Artificial Intelligence (AI) 100 Startups 2017

2017 AI 100 Companies
CB INSIGHTS AI Promising 100 Companies

3
Contents
1 Preface
2 100 Companies
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3 Appendix

Purpose
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The aim of this PPT is to catch up with the trend of Artificial Intelligence in business situations.
Nowadays, AI is a kind of buzz word, but it has a high potential.
As a business parson, it is necessary to understand what AI is and how AI affect our businesses.

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1760〜1830 1865〜1900 1990〜2000
①GPT=Steam Engine
②GPT=Internal Combustion Engine
③GPT=Internet
GPT(General Purpose Technology）
accumulation
History of Technology
2029 2045
④GPT=AI
1st industrial revolution
2nd industrial revolution
3rd industrial revolution
2029 Specific AI to General AI
4th Industrial revolution
2045 Singularity
ロジスティック曲線
https://ja.wikipedia.org/wiki/%E3%83%AD%E3%82%B8%E3%82%B9%E3%83%86
%E3%82%A3%E3%83%83%E3%82%AF%E6%96%B9%E7%A8%8B%E5%BC%8
F
We have 3 industrial revolutions.
1st one was based on the development of steam
engine. 2nd one was Internal combustion engine.
3rd one was Internet.
What is next ? I think AI is going to be 4th.

7Source: the singularity is near
The Row of Accelerating Returns
秩序が指数関数的に成長すると、時間は指数関数的に速くなる — つまり、
新たに大きな出来事が起きるまでの時間間隔は、時間の経過とともに短くなる。

The
Singularity is
Near
According to Dr. Ray Kurzweil,
It will be at 2045, and Specific AI is going to
be shifted at 2029 to general AI
owing to the development of
GNR (Genetics, Nano-technology, Robotics)
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Utopia ?
or
Dystopia ?
AI is going to be the most important subject in 21 century.

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Affectiva, an MIT Media Lab spin-off, is the pioneer in Emotion AI,
the next frontier of artificial intelligence. Affectiva’s mission is to bring
emotional intelligence to the digital world with our emotion recognition
technology that senses and analyzes facial expressions and emotion.
The patented software is built on an emotion AI science platform
that uses computer vision, deep learning and the world’s largest
emotion data repository of more than 4.9 million faces analyzed from
75 countries, amounting to more than 50 billion emotion data points.
Affectiva’s SDKs and APIs enable developers to add emotion-sensing
and analytics to their own mobile apps, games, devices, applications
and digital experiences. Affectiva is also used by more than 1,400
brands, like Kellogg's, MARS and CBS to gather insight and analytics
in consumer emotional engagement.
General :01: Facial / Emotional Analysis
Category : Facial expression analysis
Emotion-sensing technology
Emotion analytics technology
Capital : $25.17M
SeriesA: $2M
SeriesB: $5.73M
SeriesC: $12M
Rounds: 4 rounds from 5 investors
Monetize : SDK, API , Consulting
Founder: Rana el Kaliouby
Name : affectiva 2009〜
HQ: Boston
Employee: 51-100
Source : https://www.affectiva.com/
Features :
• 5.6 million faces are measured
• Used by 1,400 brands
• 22 K media units analyzed
• 38,944 of face video analyzed
• MIT spin-off
Market : Advertising, and media

14
Petuum is creating a development platform that serves the full spectrum of
Artificial Intelligence and Machine Learning applications. They empower
organizations to create AI/ML solutions that are correct, fast,scalable, and
consume minimal computing resources. Their omnisource platform
processes and integrates data in different formats such as numeric, textual,
imagery, tabular, structured or unstructured, static or streaming from diverse
sources like social media, consumer profiles, electronic health records,
sensor logs from IoT devices, transaction logs from financial systems, and
machine logs from manufacturing equipment.
It is also omni-lingual, programmable with multiple popular
languages such as Python, R, Java, C++, and Julia. It’s also omnimount,
supporting different hardware platforms such as
datacenters, workstations, laptops, mobile, and
embedded devices.management, and beyond.
General :02: ML
Category : Full spectrum AI platform
Capital : $15M
Seed :
SeriesA: $15M
SeriesB:
Monetize : Provide omni platform
Founder: Eric Xing
Name : Petuum, inc. 2016〜
HQ: Pittsburg
Employee: 11-50
Source : http://www.petuum.com/products.html
Features :
• Programmable in all language.
• Originated from CMU.
• Faster, cheaper, repeatable and
affordable.
Market : AI / ML solutions

15
Vicarious is an artificial intelligence research
company that uses the computational principles of
the brain to build software designed to think and
learn like a human. Leveraging a new computational
paradigm called the Recursive Cortical Network,
the company has developed a visual perception
system that interprets the contents of photographs
and videos in a manner similar to humans. The
research at Vicarious is expected to
have applications for robotics, medical image
analysis, image and video search, and many
other fields.
General :03: General AI
Category : General AI
Robotics
Capital :$122M
Seed :
SeriesA:$15M
SeriesB:$52M
SeriesC:$50M
Monetize : ???
Founder: Dileep George
Name : Vicarious 2010〜
HQ: San Francisco
Employee: 11-50
Source : https://www.vicarious.com/index.html
Features :
• For robotics, medical, and so on.
• General AI
• Adviser Fei-Fei Lee
• Investors
Market : General AI and robotics

16
H2O.ai is the maker behind H2O, the leading open source AI platform
for data products. With H2O, a plethora of machine learning models
(from linear models to tree-based ensemble methods to Deep Learning)
can be trained from R, Python, Java, Scala, JSON, H2O’s Flow GUI, or
the REST API, on laptops or servers running Windows, Mac or Linux, in
the cloud or on premise, on clusters of up to hundreds of nodes, on top
of Hadoop or with the Sparkling Water API for Apache Spark. Some of
H2O’s mission critical applications include fraud, anti-money laundering,
auditing, churn, credit scoring, user based insurance, ICU monitoring,
predictive maintenance, operational intelligence and more in over 7,000
organizations. H2O is brewing a grassroots culture of data transformation
in its customer communities. Customers include Capital One, Progressive,
Zurich, Transamerica, Comcast, Nielsen Catalina Solutions, Neustar,
Macy’s, Walgreens, Kaiser Permanente and Aetna.
General :04: ML
Category : ML,
Cloud Computing
Analytics
Big Data
Capital : $33.6M
Seed : $3M
SeriesA: $8.9M
SeriesB: $20M
Monetize : Open source platform
Founder: SriSatish Ambati
Name : H2O.ai 2011〜
HQ: Mountain View
Employee: 11-50
Source : https://www.h2o.ai/
Features :
• Open source AI
• Over 7000 customers
• Cisco and Paypal is included
• Bringing AI to enterprise
• World record platform for AIMarket : Machine learning in financial,
insurance, healthcare

17
Loop AI Labs’ cognitive platform Loop Q is a technology that enables
organizations in any industry to stay competitive during the Fourth
Industrial Revolution by augmenting the capacity of current workforce.
With its ability to learn, parse context and understand meaning, the Loop
Q platform reasons on dark data in any language, and applies that Human
Capacity to power Robotic Process Automation (RPA). These cognitivelyenabled
applications powering RPA are custom-built by the global network
of Loop Certified Partners, already working in the Digital Transformation of
Forbes 2000 clients in Asia, Europe and America. The Q platform is a fully
unsupervised cognitive computing technology consisting of proprietary
Human Capacity cognitive algorithms integrated into a custom-built
High Performance Computing GPU accelerated hardware. Loop Q builds
on a long history of research and articulates several disciplines of
science and technology, including linguistics, psychology, neuroscience,
supercomputing, and AI.
General :
05: Unsupervised cognitive computing
platform
Category : Personalization
ML
Neural Language Processing
Big Data
Capital : ???
Seed :
SeriesA:
SeriesB:
Rounds:
Monetize : Machine Learning
Founder: GM Calafiore
Name : Loop.ai Labs 2012〜
HQ: San Francisco
Employee: 11-50
Source : http://www.loop.ai/industries
Features :
• Loop Q
• Robotics Process Automation
• Unsupervised cognitive computing
• $200M DARPA CALO project, the largest
government-funded artificial intelligence
project in history.
Market : EC, Healthcare, media, automotive,
mobile, retail ,etc.

18
CognitiveScale builds machine intelligence software for healthcare,
commerce, and financial services markets. The company’s products—
Engage and Amplify help large enterprises increase customer engagement,
improve decision-making, and deliver self-learning and self-assuring
business processes. CognitiveScale has successfully deployed its
software with multiple Global 500 companies and has formed strategic
go to market and technology partnerships with IBM, Microsoft, and
Deloitte. CognitiveScale was founded in 2013 by highly successful serial
entrepreneurs and senior executives from IBM Watson, Oracle, and
Salesforce with deep expertise in vertical enterprise software, cloud
computing, and machine learning. The company has won numerous
awards and featured in prominent research and publications. It is
headquartered in Austin, Texas, with offices in the United Kingdom and
India. Investors include Norwest Ventures, Intel Capital, IBM Watson,
and Microsoft Ventures.
General :06: Cognitive cloud software
Category : Big Data
Dark Data
ML
Information service
Capital :
Seed :
SeriesA:
SeriesB: $40M
Monetize : enterprise cognitive cloud
Founder: Matt Sanchez
Name : Cognitive Scale
HQ: Austin
Employee: 51-100
Source : https://www.cognitivescale.com/technology/
Features :
• Focus on dark data
• 500 companies
• Partner IBM, Microsoft, Delotte
Market : Commerce, healthcare, finance

19
Sentient’s mission is to transform how businesses
tackle their most complex, mission-critical problems
by empowering them to make the right decisions
faster. Sentient’s technology has patented
evolutionary and perceptual capabilities that will
provide customers with highly sophisticated solutions,
powered by the largest computer infrastructure
dedicated to distributed artificial intelligence.
General :07: Distributed AI Platform
Category : EC
Digital Marketing
Software
Capital : $143M
Seed :
SeriesA:
SeriesB: $38M
SeriesC: $103.5M
Monetize : Providing AI software
Founder: Antoine Blondeau
Name : Sentient 2007〜
HQ: San Francisco
Employee: ???
Source : https://www.sentient.ai/
Features :
• Decision making tool
• Personalization
• Sentient AWARE
• Sentient ASCEND
Market : digital marketing, EC, finance

20
Founded in 2012, Voyager Labs developed core technology with
unprecedented capabilities for analyzing in real time billions of data
points worldwide from multiple sources in order to understand and
predict human and group behavior and create real-time
actionable insights.
The company’s cognitive computing deep-insights platform
features unprecedented capabilities for analyzing in real-time billions
of publicly available unstructured data points. With offices in New
York, Washington and London, and R&D center in Israel, the
company currently employs more than 90 employees.
General :08: Big Data Analysis
Category : Personalization
Big Data
Platform
Capital : $100M
Seed :
SeriesA:
SeriesB:
Monetize : Optimization
Founder: Avi Korenblum
Name : Voyager lab
HQ: New York
Employee: 51-100
Source : http://voyagerlabs.co/
Features :
• Unprecedented capabilities for analyzing in
bunch of data.
• Gain insights into human behavior, interest,
and internet using data.
Market : EC, finance, human analysis

21
Numenta’s mission is to be a leader in the new era of machine
intelligence. They believe the brain is the best example of an
intelligent system, providing a roadmap for building intelligent
machines. The brain’s center of intelligence, the neocortex,
controls a wide range of functions using a common set of
principles. Numenta has developed several HTM example
applications to demonstrate the wide applicability of their
technology. They put all of their research and software
implementations into open source and encourage others to
join us in building a community. From a commercial point of
view, they license their technology and intellectual property.
General :09: BI
Category : Neuroscience
Machine Intelligence
Capital : ???
Seed : ???
SeriesA: ???
SeriesB: ???
Rounds: ???
Monetize : Licensing
Founder: Jeff Hawkins
Name : Numenta 2005〜
HQ: Redwood City
Employee: 15-20
Source : https://www.numenta.com/
Features :
• cohesive theory, core software technology, and
numerous applications
• Creating intelligent machines
• Neuroscience research
• Open source community
Market : Business Intelligence
Enterprise software

22
Scaled Inference is enabling a new generation of intelligent
software built by the masses and powered by an open shared
platform.
Easily enhance user’s websites, apps, and other software to
intelligently optimize for the key performance metrics, far faster
than possible with traditional analytics or A/B testing. Harness
the true power of Artificial Intelligence and Machine Learning,
with seamless integration and unprecedented versatility and
ease of deployment.
General :10: Scalable AI
Category : Machine Learning,
Probabilistic Inference
Distributed Systems
Capital : $13M
Seed : $5M
SeriesA: $8M
SeriesB:
Monetize : Intelligent Computing
Founder: Olcan Sercinoglu
Name : Scaled Inference 2014〜
HQ: Polo Alto
Employee: 11-50
Source : https://www.scaledinference.com/
Features :
• A platform for pattern recognition,
detection, prediction, and so on.
• Providing APIs
Market : ML, BI

23
Skymind is the Red Hat of artificial intelligence. It provides support,
training and services around an enterprise distribution of its
opensource libraries called the Skymind Intelligence Layer (SKIL).
These libraries include Deeplearning4j, the most widely used deep learning
tool for Java; and the scientific computing library ND4J, or n-dimensional
arrays for Java (Numpy for the JVM). Deep learning can equal and
surpass expert human accuracy on many pattern recognition tasks,
and Skymind is applying it to old, hard business problems such as
fraud detection, network intrusion detection, hardware breakdown
prediction, churn prediction, market forecasting and image recognition.
Skymind’s customers are in such sectors as financial services
, telecoms, manufacturing, healthcare and retail. Skymind’s
open-source software integrates with the rest of the AI stack,
working with tools such as Hadoop, Spark, Kafka, and ElasticSearch.
Skymind works with large clients on-premise and in the hybrid
cloud to ensure data privacy and security
General :11: BI
Category : deep learning,
prediction,
data analysis,
BI,
Data mining
Capital : $3.32M
Seed : $3.3M
SeriesA:
SeriesB:
Monetize : Providing support,training and service
Founder: Adam Gibson
Name : skymind 2014〜
HQ: San Francisco
Employee: 11-50
Source : https://skymind.ai/
Features :
• Working with Hadoop, Spark, kafka
• Deeplearning4j.org : the world's first open-source,
distributed, commercial-grade deep-learning framework.
• Investors : fundersClub, Y Combinator
Market : Security, Prediction, Image, Finance

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Digital Reasoning is a leader in cognitive computing. They build software
that understands human communication and extracts insights from
it - in many languages, across many domains, and at enormous scale.
Their award-winning cognitive computing platform, Synthesys®, is
able to analyze all forms of unstructured and structured data, including
feeds from legacy technologies, as well new insights from untapped
resources. It produces holistic insights that give organizations
unparalleled oversight and control, even at the scale of complex global
enterprises and government departments. Synthesys uses natural
language processing and machine learning to semantically analyze
human communication, uses context to discern meaning and relevance,
and applies knowledge representation to adapt to different usage
domains. It creates and maintains profiles of entities (people, places,
objects) and relationships between them. Machine learning continually
improves its accuracy. Digital Reasoning has applied Synthesys to
develop proven solutions for financial services, intelligence and defense,
law enforcement, and health care organizations.
General :12: Cognitive computing
Category : NLP,
ML,
Big Data,
Text Analytics
Capital : $73.96M
Seed :
SeriesC: $24M
SeriesD: $40M
Monetize : providing software
Founder: Tim Estes
Name : Digital Reasoning 2000〜
HQ: Franklin
Employee: 101-250
Source : http://www.digitalreasoning.com/
Features :
• Software that can understand
human communication.
• NLP and ML
• Goldman Sachs and NASDAQ
Market : research and development in
cognitive computing

25
Bonsai is a software development platform that empowers every developer
to build, teach and use intelligence models. The Bonsai Platform abstracts
away the low-level, inner workings of artificial intelligence so developers
can focus on what really matters, building smarter applications faster.
Instead of needing expertise in complex AI algorithms and techniques, the
Bonsai Artificial Intelligence Engine allows a developer to more efficiently
code the multiple concepts and lessons needed to enable greater control
and optimization of hardware and software. Bonsai’s fundamentally
different approach results in far more accessible, efficient and explainable
models compared to alternatives. Bonsai is headquartered in Berkeley, CA
and backed by NEA.
General :13: Developer platform
Category : Operating Systems,
Developer Tools,
Developer Platform,
Machine Learning
Capital : $13.62M
Seed : $320K
SeriesA: $13.3M
SeriesB:
Monetize : B2B industrial strength AI for developers
Founder:
Name : bonsai 2014〜
HQ: Berkeley
Employee: 11-50
Source : https://bons.ai/
Features :
• For developer platform
• Industrial specific AI
• Investors : Microsoft ventures,
Samsung ventures
Market : developers

26
Ayasdi helps companies around the world to use artificial intelligence
and Big Data to make employees hundreds of times more productive
and to drive fundamental breakthroughs that are beyond the capabilities
of humans. Their revolutionary machine intelligence platform leverages
automation, machine learning and topological data analysis to simplify
the extraction of knowledge from even the largest and most
complex data sets and to facilitate the deployment of intelligent,
AI-based applications across the enterprise. Developed by Stanford
computational mathematicians, Ayasdi’s unique approach to machine
intelligence leverages breakthrough mathematics, highly automated
software and inexpensive, scalable computers to revolutionize the
process of converting big data into business impact. They are excited to
count many of the Global 500, plus leading governments and research
institutions as their clients and partners.
General :14: BI
Category : Big Data,
ML,
Data Visualization,
Detection
Capital : $106M
Seed : ???
SeriesA: $10M
SeriesB: $30.6M
SeriesC: $55M
Monetize : Providing TDA
Founder: Gurjeet Singh
Name : AYASDI 2008〜
HQ: Menlo Park
Employee: 10-50
Source : https://www.ayasdi.com/
Features :
• B2B focus
• Automated, inexpensive, and scalable
• Topological Data Analysis (TDA).
TDA: The most significant technological
advancements ever funded by DARPA
• Anti-money laundering, BI, fraud, management, etc
Market : Financial, Public, Healthcare

28
Textio empowers you to be the best writer you can be, by predicting how
well your content will perform before you ever publish it. Textio is built on
predictive engine technology that combines machine learning and natural
language processing with a customer data exchange. The result is a
learning loop that joins artificial intelligence to human creativity,
becoming smarter with every keystroke. Textio’s first domain focus is on
content for recruiting and hiring such as job posts and candidate
emails. Textio scores your writing and highlights your most statistically
significant phrases, and then offers clear guidance to help you improve
your document’s performance. Case studies show that companies using
Textio will attract a cohort of job applicants that is on average 24% more
qualified and 12% more diverse than those applying to the competition
— and Textio customers fill positions on average 17% faster.
General :15: NLP
Category : Text Analytics,
Natural Language Processing,
ML
Capital : $29.5M
Seed : $1.5M
SeriesA: $8M
SeriesB: $20M
Monetize : providing text checking software
Founder: Kieran Snyder
Name : textio 2014〜
HQ: Seattle
Employee: 11-50
Source : https://textio.com/
Features :
• User : Microsoft, Square, Twitter,
Starbucks, Apple, Slack, NASA,
P&G etc.
• NPL × Predicting processing engine
• Founder is ex-Microsoft
Market : Hiring advertisement
“We had this premise that word processing
in text hadn’t been disrupted in a while, from
command line to GUI. We had the internet come
along, it was about social and sharing, and we
think that AI and the set of related technologies is
the next big disruptor of text. If you know the
Performance of a document before it’s ever
published then you can fix it before it’s published.”
CEO Kieran Snyder

29
Fido Artificial Intelligence turns a decision-making process into a
conversation. It learns automatically by extracting facts and opinions
from articles, blogs, social media and more. Fido Decision Engine
is used for a wide range of applications, including: fact-checking,
making decisions in hospitality and travel, e-commerce and more;
answering healthcare questions based on clinical data, patient and
doctor conversations etc.; product development and marketing. Fido
has married symbolic approach known for the highest precision
and predictability with self-learning neural networks. This patented
approach enables to understand the English language without the
“human bottleneck” - the need for training or labeling data for specific
domains of expertise. Fido.ai is a spinoff from AI Lab in Europe, that has
developed this new hybrid approach while building bots and AI products
for Fortune 500 companies and govements. Meet Ada, a Bot that reads
and learns from reviews.
General :16: NLP
Category : text analyzing,
Big Data
Capital : $1.86M
Seed : $1.86M
SeriesA:
SeriesB:
Rounds: 1 round from 8 investors
Monetize : Providing chatbot
Founder: Michal Wroczynski
Name : fido.ai 2013〜
HQ: San Mateo
Employee: 11-50
Source : http://fido.ai/
Features :
• Video: youtube.com/watch?v=FkM1foMZm7U
• Decision making process into a conversation
• Self learning neural network
• Powering chatbots
• Answering business questions based on a large volume of text
• Cyberbullying and hate speech detection.
• Invester : Plug and Play
Market : Communication, SNS

30
Cortical.io offers Natural Language Understanding (NLU) solutions
based on Semantic Folding, a theory which opens a fundamentally new
perspective to handling Big Text Data. Inspired by the latest findings
on the way the brain processes information, Cortical.io’s Retina Engine
converts language into semantic fingerprints, a numerical representation
that captures meaning explicitly and operates on it computationally. The
Retina Engine compares the semantic relatedness of any two texts by
measuring the overlap of their fingerprints. It can be easily customized for
any language, domain or jargon and delivers results quickly, at low costs.
The intrinsic difference of Cortical.io’s algorithm makes it possible to
solve many open NLU challenges like meaning-based filtering of terabytesof
unstructured text data, real-time topic detection in social media or
semantic search over millions of documents across languages. Cortical.io
was founded in 2011 in Vienna, Austria and holds a broad general license
for Numenta’s HTM technology
General :17: NLU
Category : Semantic Fingerprints,
Classification,
Streaming Text Filter,
Keyword extraction,
NLP,
Text Analytics
ML
Capital : $6.18M
Seed : $3M
SeriesA: $1.8M
SeriesB:
Monetize : APIs, Ratina platform
Founder: Francisco Webber
Name : Cortical.io 2011〜
HQ: Austria
Employee: 11-50
Source : http://www.cortical.io/
Features :
• NLU from bid text data
• Semantic Folding
• Cortical.io’s Retina Engine converts language into semantic fingerprints
• Solve these problems :
meaning-based filtering of terabytes of unstructured text data, real-time topic
detection in social media or semantic search over millions of documents
across languages.
Market : BI

31
Narrative Science is the leader in Advanced NLG for the enterprise. Its
Quill™ platform, an intelligent system, analyzes data from disparate
sources, understands what is interesting and important, then automatically
generates perfectly written narratives to convey the right meaning from
the data for any intended audience, at machine scale. It excels where
data
visualizations fall short: it identifies and conveys relevant information
in conversational language that people can immediately comprehend,
trust and act on. Organizations rely on Narrative Science to better serve
customers with useful written content and to increase efficiency, freeing
employees to focus on high-value activities and innovation.
General :18: NLG
Category : Neural Language Generation
Big Data
Capital : $40.4M
Seed :
SeriesB: $6M
SeriesC: $12M
SeriesD: $22M
Monetize : Providing NLG platform
Founder: Stuart Frankel
Name : NarrativeScience 2010〜
HQ: Chicago
Employee: 51-100
Source : https://narrativescience.com/Platform
Features :
• Neural Language Generation
• Intelligent Narratives
• Quill advanced NLG platform
Market : Finance, BI, Government, Retail

33
Nanit is the first baby-safe monitor that uses computer vision
technology to measure sleep and provide scientifically backed insights
for parents to help their babies sleep better — all without a wearable.
Nanit was developed in conjunction with doctors and sleep experts
to ensure the device tracks the most important metrics. The camera
provides a high-resolution bird’s eye view of the crib, and its sensors
can measure and differentiate between even the slightest behavioral
changes. Nanit’s AI gradually familiarizes itself with baby’s behavior
over time and delivers personalized insights to help improve sleep.
Nanit is the only monitor on the market that provides sleep insights,
behavioral analysis, parenting tips, social sharing capabilities and nightly
video summaries. Other features include a private social feed for parents
and caregivers to communicate; floor stand with easy installation; night
light and white noise maker; fully integrated cable management system;
and humidity/temperature sensors.
General :19: IoT
Category : Smart monitor,
ML,
Capital : $6.6M
Seed : $6.6M
SeriesA:
SeriesB:
Monetize : Selling devices
Founder: Assaf Glazer
Name : nanit 2015〜
HQ: New York
Employee:11-50
Source : https://www.nanit.com/
Features :
• $349 per unit.
• Baby safe monitor.
• Understand sleep patterns, parent visits, room
conditions and much more.
• 30 days free trial.
Market : Baby, Child care

34
Munich-based IIoT company KONUX combines sensor data and artificial
intelligence to generate real-time insights into the health of machines
and infrastructure. This holistic approach enables operators to analyze
machine problems and predict maintenance needs ahead of time.
Clients benefit from decreases in maintenance costs of up to 30% and
reductions in machine breakdowns of up to 70%. The KONUX solution
replaces outdated manual inspection methods with smart sensors that
continuously transmit asset condition data to the KONUX Andromeda
software platform. There, the data is analyzed using machine learning
algorithms and visualized using a customized front end. The system
notifies of critical events in real time and gives recommendations
for optimal planning of maintenance operations. KONUX is currently
digitizing Deutsche Bahn’s high-speed railway network through
condition monitoring of switches nationwide. This helps Deutsche Bahn
significantly reduce inspection and maintenance costs, decrease train
delays and improve worker safety.
General :20: IIOT
Category : Smart Sensor
ML
Capital : $18.5M
Seed : $2M
SeriesA: $16.5M
SeriesB:
Monetize : smart IoT sensors and Visualizing
Founder: Andreas Kunze
Name : KONUX 2014〜
HQ: Munchen
Employee:11-50
Source : https://www.konux.com/
Features :
• Industrial IoT
• Visualizing and Predicting the industrial world.
• Sensors data to actionable insights.
Market : Transportation

35
Verdigris is an artificial intelligence and IoT platform that
makes buildings smarter and more connected while reducing
energy consumption and costs. By combining proprietary hardware
sensors, machine learning, and software, Verdigris “learns” the
energy patterns of a building. Their software produces comprehensive
reports including energy forecasts,alerts about faulty equipment,
maintenance reminders, and detailed energy usage information for
each and every device and appliance. Verdigris offers a suite of
applications that gives building engineers a comprehensive overview,
an “itemized utility bill”, powerful reporting, and simple automation
tools for their facility.
General :21: IIOT
IoT platform
IoT hardware
Capital : $16M
Seed : $3.4M
SeriesA: $12.7M
SeriesB:
Monetize : Hardware and software for analysis
Founder: Jonathan Chu
Name : Verdigris Technologies 2011〜
HQ: Moffett Field
Employee: 11-50
Source : http://sightmachine.com/product/
Features :
• IoT platform
• Energy management, Property management.
Energy efficiency, Operational efficiency.
• Get better data, and smart decision, then save
money.
• Cool UI
Market : Energy management, big data

36
Sight Machine is the category leader for manufacturing analytics
and used by Global 500 companies to make better, faster decisions
about their operations. Sight Machine’s analytics platform, purpose-built
for discrete and process manufacturing, uses artificial intelligence,
machine learning, and advanced analytics to help address
critical challenges in quality and productivity throughout the
enterprise. The platform delivers “AI for the plant floor” and is
powered by the industry’s only Plant Digital Twin (patent pending)
, which enables real-time visibility and actionable insights
for every machine, line, and plant throughout an enterprise.
Founded in Michigan in 2011 and expanded to the Bay Area in 2012,
Sight Machine fuses the spirit of Silicon Valley technology innovation
with rock-solid Detroit manufacturing. Its team includes the founders
of Slashdot along with leadership from early Yahoo, Palantir, Tesla,
Cisco, IBM, McKinsey, and Apple.
General :22: IIOT
Category : Manufacturing analysis,
ML
Robotics,
SaaS
Capital : $30.52M
Seed :
SeriesA: $5M
SeriesB: $20M
Monetize : Analysis and Solutions
Founder: Jon Sobel
Name : SightMachine 2012〜
HQ: San Francisco
Employee: 51-100
Source : http://sightmachine.com/
Features :
• Reducing energy consumption and cost.
• Quality ↑, Productivity ↑, Visibility ↑
• Sensor for many industries.
• Kaizen culture.
• Real time visualizing
Market : Aerospace, Automobile, CPG,
Electronics, Food, Oil, Gas, Medical

38
The BloomReach Personalization Platform is an underlying set of
technologies to deliver the right experience for the user and business in
every digital context from acquisition to conversion. The BloomReach
Personalization Platform powers big data applications that span the
customer experience and make it more personalized and relevant
to the customer’s intent. The BloomReach Personalization Platform
centralizes data enrichment, access, publishing and integration across
all BloomReach products. With a single integration, customers have one
login to access all BloomReach products, one pixel to inform BloomReach
and one feed to send to BloomReach. Data enrichment includes attribute
extraction, synonymization and machine learning. Data access makes
the behavioral, product and demand data available to all BloomReach
applications. Publishing supports the integration of many different widgets
into a single framework so that customers can customize their templates
and experiences.
General :23: EC Personalization
Category : EC,
SEO,
ML,
CMS
Capital : $97M
Seed :
SeriesA: $5M
SeriesB: $11M
SeriesC: $25M
SeriesD: $56M
Monetize : Software (Personalization, Platform))
Founder: Raj De Datta
Name : bloomreach 2009〜
HQ: Mountain View
Employee: 251-500
Source :
Features :
• Personalization platform
• Hippo CRM, cloud, marketplace
• BIMarket : CMS

39
mode.ai’s interactive user-experience and interface capitalizes
on users’own holistic and subjective notions of similarity.
mode.ai’s AI is uniquely suited to facilitate visually-driven,
conversational experiences. Mode.ai is in the business of
building AI-powered visual bots for retailers and publishers
(B2B2C offering) using computer vision and deep learning,
to provide an innovative conversational commerce channel
on mobile messaging platforms. Their technology invites
users to find visually similar items (‘more like this’), get styling
suggestions (‘wear it with’), experience virtual reality
(‘show on me’) and much more.
General :24: EC chatbot
Category : Retail,
Visual Search,
Commerce
Capital : ???
Seed : ???
SeriesA:
SeriesB:
Rounds: 1 round from 1 investor
Monetize : Chatbot × charge
Founder: Eitan Sharon
Name : mode.ai
HQ: Polo Alto
Employee: 1-10
Source : http://mode.ai/#/menu
Features :
• Chatbot AI in fashion
• Interactive EC
Market : EC

41
Cape Analytics was established to change the way information about the
human-built environment is created and used. The company uses artificial
intelligence to instantly and automatically extract proprietary property
data from geospatial imagery. Cape Analytics’ cloud-based platform uses
computer vision to provide near inspection-quality information about
high-value property features – instantaneously and at scale. This data is
available nationwide and can be easily integrated by insurance carriers and
other property stakeholders. Cape Analytics establishes a new category of
property analytics, offering immediacy and coverage comparable to public
record data, but with the accuracy and detail previously available only from
time-consuming, in-person property assessments.
General :26: Image recognition
Category : Image recognition
ML
Capital : $14M
Seed :
SeriesA:
SeriesB:
Monetize : Data analysis
Founder: Ryan Kottenstette
Name : CAPE ANALYTICS 2014〜
HQ: Mountain View
Employee: 11-50
Source : https://capeanalytics.com/
Features :
• geospatial imagery
• Focus on property data
• Using public recorded data
• Data Instant, Accurate, Everywhere
without inspectorsMarket : Insurance

42
Kensho is empowering financial institutions with technology that
brings transparency to markets. Kensho is pioneering real-time
statistical computing systems and scalable analytics architectures—the
next generation of improvements to the global financial system. Kensho
harnesses massively-parallel statistical computing, user-friendly visual
interfaces and breakthroughs in unstructured data engineering and
predictive analytics to create the next-generation analytics platform for
investment professionals. Addressing the most significant challenges
surrounding investment analysis on Wall Street today-achieving speed,
scale, and automation of previously human-intensive knowledge
work-Kensho’s intelligent computer systems are capable of answering
complex financial questions posed in plain English, and in real-time.
General :25: ML
Category : ML,
Data Analytics
Capital : $67M
Seed : $10M
SeriesA: $7M
SeriesB: $50M
Monetize : Analytics Software
Founder: Daniel Nadler
Name : KENSHO 2013〜
HQ: Cambridge
Employee: 51-100
Source : https://www.kensho.com/industry/as
Features :
• Real time statistical system
• Financial Analytics Software deploys scalable
analytics systems
• Partner: Goldman, J.P Morgan, Bank of America
CITI, Morgan Stanley
Market : Insurance, Financial, Healthcare,
Security

43
Numerai is a new kind of hedge fund built by a network of data
scientists. Numerai manages an institutional grade long/short global
equity strategy for the investors in their hedge fund. They transform
and regularize financial data into machine learning problems for their
global community of data scientists. In December 2015, they created
the world’s first encrypted data science tournament for stock market
predictions. The most accurate and original machine learning models
from the world’s best data scientists are synthesized into a collective
artificial intelligence that controls the capital in Numerai’s hedge
fund. They reward outstanding contributions from the data science
community with Bitcoin.
General :27: Platform
Category : ML,
Data Science
Capital : $7.5M
Seed :
SeriesA: $6M
SeriesB:
Monetize : ???
Founder: Richard Craib
Name : NUMERAI 2015〜
HQ: San Francisco
Employee: 11-50
Source : https://numer.ai/
Features :
• A new kind of hedge fund built by a network of data
scientist
• Numeaire : First cryptocurrency made by hedge fund
• On the Ethereum
• Network effect × financeMarket : Finance , Stock market
Data scientists entering Numerai’s tournament currently receive,
weekly, an encrypted data set that is an abstract representation of
stock market information that preserves its structure without revealing
details. The scientists then create machine-learning algorithms to find
patterns in that data, and they test their models by uploading their
predictions to the website, which so far has received about 40 billion
Predictions.
Forbes
https://vimeo.com/205032211

44
AlphaSense solves the crippling information overload problem for
knowledge professionals who are subject to a fire hose of data and are
unable to catch or digest the vast amounts of content relevant to their
daily decisions. Some platforms offer access to relevant documents,
but none have intelligent search capabilities. AlphaSense offers access
to proprietary research databases and includes semantic knowledge of
financial language and the relevance analytics to surface valuable hidden
snippets of information. AlphaSense ingests millions of documents,
including company filings and transcripts, presentations, news,
press releases and Wall Street research and any uploaded content. It
semantically indexes these documents and produces instant results for
users on any theme they are researching, summarizing relevant snippets
across a vast volume of documents. The key benefit AlphaSense provides
is an information edge, allowing users to find what others miss, and be the
first to act on new information and insights.
General :28: NLP search engine
Category : Intelligent Search Engine
Capital : $35M
Seed : $1.7M
SeriesA:
SeriesB:
Monetize :
Founder: Raj Neervannan
Name : alphasence 2010〜
HQ: New York
Employee: 51-100
Source : https://www.alpha-sense.com/#whyalpha
Features :
• Solve the crippling info. overload problem
• Find critical info.
• Access +35,000 companies.
• Linguistic search algorithms access to M of documents
Market : Finance

45
KAI, a conversational AI platform, enables companies to engage and
transact with their customers via intelligent conversations, anytime,
anywhere. KAI Banking is fluent in banking with thousands of intents and
millions of banking sentences. Financial institutions power smart bots on
messaging platforms like Facebook Messenger and virtual assistants in
their mobile apps to fulfill requests, solve problems, and predict needs for
their customers. KAI-powered bots and assistants help with payments,
transaction and account insights, and personal finance management.
They also provide new ways for banks to support and market product
and services. The experience is as natural as texting a friend because
KAI understands human-like conversations including idiosyncratic
phrases, rapid topic changes and interruptions. KAI keeps track of the
flow of conversations versus just natural language understanding –
staying focused on customers’ goals and interpreting the context of a
conversation. It enables lifestyle banking with financial decisions woven
into everyday life.
General :29: NLP chatbot
Category : Chatbot,
NLP,
Fintech
Capital : $11.45M
Seed : $2.25M
SeriesA: $9.2M
SeriesB:
Monetize : providing AI chatbot
Founder: Zor Gorelov
Name : kasisto 2013〜
HQ: New York
Employee: 11-50
Source : http://kasisto.com/
Features :
• Interactive chatbot
• For bank (payment, transactions, and account insights)
• Message on messenger
• Prefer: voice, touch, and text
Market : Financial (Bank)

47
Gigster puts a world-class software development team in your pocket.
Software is becoming an essential tool for every business with global IT
spend reaching $2.3T, yet very few have easy access to quality, managed
talent when they need custom software. Gigster is changing the way
software is created by building the perfect team for every project,
giving clients a single point of contact with their product manager,
and completing it for a fixed price. The emerging viability of artificial
intelligence and data science have recently made this possible. Intelligent
tools powered by data from thousands of past projects take Gigster
freelancers, already among the best in the world, to superhuman levels of
efficiency. Gigster was founded in 2014 and has worked with companies
from seed-stage startups to enterprises like IBM, World Bank, Airbus,
Square, and Mastercard. Gigster has raised $12M from Andreessen,
Greylock, Bloomberg, and Y Combinator.
General :30: Smart developing service
Category : App development,
Web development,
Rapid Prototyping,
Product Management
Capital : $32.5M
Seed : $2.5M
SeriesA: $10M
SeriesB: $20M
Monetize : software developing platform
Founder: Roger Dickey
Name : Gigster 2014〜
HQ: San Francisco
Employee: 11-50
Source : https://gigster.com/
Features :
• Investors: Andreessen, Y Combinator
• smart development service
• 700+ network, 100+ project, 5M line of code
• Reliability and Efficiency
Market : developers

48
Prospera is developing artificial intelligence for agriculture to transform
farming from an intuition-based practice to one that will use statistical
models and automation in a way similar to silicon chip manufacturing,
with protocols that optimize workforce, irrigation, fertilization and
spraying. With in-field cameras and climatic sensors, Prospera is the
only company that offers accurate remote agronomy and management
solutions to farmers around the world. With an end-to-end data sciences
approach to acquire, analyze and turn all in-field data into actions,
growing practices will be measured more accurately, and “growing
campaigns” will be more similar to today’s advertising campaigns
in terms of understanding ROI, bench-marking and optimization. By
measuring and analyzing the finite variables which affect crops in
greenhouses and farms, Prospera offers solutions to empower farmers
with real-time and predictive analysis on what is happening to their
crops from a leaf by leaf basis to a multi-field basis, allowing them to
tackle critical issues of underperforming fields.
Category : ML,
Image recognition,
Computer Vision Technology
Capital : $22M
Seed :
SeriesA: $7M
SeriesB: $15M
Monetize : Providing agriculture solutions
Founder: Daniel Koppel
Name : prospera
HQ: Tel Aviv
Employee:11-50
Source : http://prospera.ag/
Features :
• Only one that offers accurate remote
agronomy and management solutions to farmers
• Centralized visibility and control
• 95% accurate yield predictions
• Maximize labor productivity
• analyze plant health, development and stress
Market : Agriculture

49
Citrine hosts the world’s largest materials repository platform. Citrine
uses this platform to build AI software that enables more efficient
discovery, optimization, manufacturing, and deployment of materials.
Their software platform ingests structured and unstructured materials
data from a wide variety of sources, both public and private; they
then use AI engines to identify important signals in those data and
directly enhance customers’ R&D and manufacturing efforts. They
serve organizations that rely on cutting-edge materials for competitive
advantage, in industries ranging from automotive, aerospace, consumer
goods, batteries, and electronics.
General :32: Predictive intelligence
Advanced material,
Analytics,
ML
Capital : $7.6M
Seed :
SeriesA: $7.6M
SeriesB:
Monetize : platform for material and chemical
Founder: Greg Mulholland
Name : Citrine 2013〜
HQ: Redwood city
Employee: 11-50
Source : https://citrine.io/
Features :
• Repository platform
• R&D and manufacturing
• operating system for advanced materials
and chemicals
• understands large-scale data from countless
sources, such as patents, research papers,
technical reports, and existing databases
Market : R&D, Product Management, chemical

50
Blue River Technology creates and delivers advanced
technology for better agriculture. The company’s pioneering
approach utilizes computer vision and robotics to build a future
that ‘makes every plant count’ - where the needs of each plant
are precisely measured and instantly responded to,
significantly reducing chemical and nutrient use. The company
brings substantial experience in precision agriculture, robotics,
computer vision and machine learning.
Category : robotics,
ML,
Capital : $30M
Seed :
SeriesA: $13M
SeriesB: $17M
Rounds:
Monetize : providing ag solutions
Founder: Jorge Heraud
Name : Blue River 2011〜
HQ: Sunny Vale
Employee: 51-100
Source : http://www.bluerivertechnology.com/
Features :
• Reduce chemical and nutrient use
• 90% lower chemical costs.
• 2.5B potential reduction in global herbicide
use.
• See & Spray: precisely spraying chemicals
only where needed, and with exactly what's
needed
Market : Agriculture

51
ROSS Intelligence uses artificial intelligence to allow attorneys to do
more than was ever humanly possible and focus on what matters most
– their clients. Co-founded in 2014 by Andrew Arruda, Jimoh Ovbiagele
and Pargles Dall’Oglio, ROSS developed a proprietary framework,
LegalCognition and has combined with IBM Watson, an early partner
of ROSS Intelligence. ROSS’ first legal A.I. went live in the area of legal
research, allowing attorneys to perform tedious research tasks in seconds
rather than hours. A graduate of Y Combinator’s 2015 class and NextLaw
Labs, ROSS is currently partnered with a variety of in-house teams, bar
associations, and law schools, and has a client base that includes Dentons,
the world’s largest law firm by headcount, and Latham & Watkins, the
world’s largest law firm by revenue.
General :34: NLP law
Category : ML,
NLP,
Lawyer
Capital : ???
Seed : $120K
SeriesA:
SeriesB:
Rounds:
Monetize : providing solutions for lawyer
Founder: Andrew Arruda
Name : ROSS intelligence 2014〜
HQ: San Francisco
Employee: 11-50
Source : http://www.rossintelligence.com/%22%20%5Ct%20%22_blank
Features :
• Investors : Y Combinator
• Legal cognition
• IBM Watson
• First AI for law
Market : law

52
Zymergen is a technology company unlocking the power of biology.
Zymergen has developed a proprietary platform, which uses robots and
machine learning to engineer microbes faster, more predictably, and to
a level of performance previously unattainable. These microbes, and the
products they produce, have broad applications across industries
such as chemicals and materials, agriculture, and healthcare.
Zymergen works with customers in these industries to improve the
economics of existing products, bring new products to market faster,
and to develop entirely new products.
General :35: ML biology
Category : Bioinformatics,
ML,
Robotics
Capital : $174M
Seed : $2M
SeriesA: $42.14M
SeriesB: $130M
Monetize : microbes
Founder: Joshua Hoffman
Name : zymergen 2013〜
HQ: Emeryville
Employee: 101-250
Source : https://www.zymergen.com/about/
Features :
• Focus on biology
• Robots and machine learning to engineer
microbes.
• Investor : SoftBank seriesB lead
Market : Biology

53
Founded in 2014, Descartes Labs is a New Mexico-based technology
company advancing the science of forecasting. The team, which
originally spun out of Los Alamos National Lab, developed a platform
that applies machine learning to massive data sets, like satellite
imagery, for forecasting and analysis across different industries.
Descartes’ first application was in agriculture, analyzing satellite
imagery to predict corn and soy yields in the U.S. ahead of the USDA,
which is the current industry benchmark. Descartes Labs’ mission is to
solve the most challenging forecasting problems today, to help us
better understand the Earth and prepare for the future. The company
was named one of CB Insights’ Game
Changers in 2016.
General :36: Image recognition agriculture
Category : ML,
Computer vision,
Geospatial,
Image recognition
Capital : $38.28M
Seed : $3M
SeriesA: $5M
SeriesB: $30M
Monetize : Selling analysis to ag companies
Founder: Mark Johnson
Name : Descartes Labs 2014〜
HQ: New Mexico
Employee: 11-50
Source : https://www.descarteslabs.com/
Features :
• building a data refinery for satellite imagery.
• Geovisual search
Center Pivot, Airport runways, Wind turvines
• Map
• ForcastMarket : Agriculture

54
Gradescope is using AI to help instructors grade their students’ work.
Instructors do not need to compromise on assessment quality — their
software lets instructors give out their existing paper-based exams or
homework assignments, but then grade them online. Instructors save
time, while grading consistently and transparently. Students get rich,
personalized feedback in a shorter amount of time. They also keep
track of the exact reason behind every point earned by every student on
every question. This enables unprecedented data analytics: for example,
they can reveal which concepts a student needs help with, or which
questions are too difficult. To date, Gradescope has been used to grade
over 12 million pages of student work at more than 200 institutions
worldwide.
General :37: Image recognition education
Category : skill assessment,
image recognition
Capital : $2.5M
Seed : $2.5M
SeriesA:
SeriesB:
Monetize : providing software to institutes
Founder: Pieter Abbeel
Name : gradescore 2014〜
HQ: Berkley
Employee: 1-10
Source : https://www.gradescope.com/
Features :
• Help instructors to grade
students’ work.
• 12 million pages of student work
• 300↑ institutes
Market : Education

55
Talla gives you the power to turn your chat platform into a command
center for your company. Talla combines the tools, processes, and
intelligent automation you need to manage information workflows
within messaging systems, including Slack. Use Talla to enable
business processes in chat, such as onboarding employees,
training on new skills, polling, and building out custom
experiences. You’ll be able deliver and gather important
information for your team, keeping everyone knowledgeable,
engaged, and productive. Founded in 2015, Talla is based in
Cambridge, MA.
General :38: Data Analysis for HR
Category : HR,
Data Analysis
Capital : $12.33
Seed :
SeriesA: $8.3M
SeriesB:
Monetize : Providing talla for $149 / $499 per month
Founder: Rob May
Name : talla 2015〜
HQ: Brookline
Employee: 11-50
Source : https://talla.com/
Features :
• Virtual assistant for working.
• automate repetitive requests, increase employee
engagement, and accelerate information retrieval.
• 2000+ Companies use it.
• Talla for IT and HR
Market : HR

57
Freenome is building software to understand the changes in plasma
cell-free DNA (cfDNA) patterns over time. By studying normal cfDNA
dynamics Freenome discovered signatures for early cancer detection
that outcompete existing screening methods from a single blood draw
in Prostate, Lung, Colorectal, and Breast cancers. In addition, the deep
learning models have been leveraged to distinguish disease subtypes such
as castration-sensitive from castration-resistant prostate cancer. Thus, the
resolving power of Freenome’s software enables both disease diagnosis
and personalized treatment recommendation from the same platform.
Freenome raised $5.5M from Andreessen Horowitz, Founders Fund, and
DCVC, and partnered with UCSF, Stanford, Duke, Emory, NYU, and several
other centers to expand the validation of Freenome’s technology.
General :
39: Image recognition for
healthcare
Category : DL,
Image recognition,
Capital : $77.55M
Seed : $5.55M
SeriesA: $72M
SeriesB:
Monetize : disease detecting solutions
Founder: Gabriel Otte
Name : freenome 2015〜
HQ: San Francisco
Employee: 11-50
Source : https://www.freenome.com/
Features :
• Investor: Andreessen Horowitz
• Image recognition for DNA
• health technology bringing accurate, accessible
and non-invasive disease screenings
• The members are scientists and technologists.
Market : Healthcare

58
We have built a Clinical AI Platform that is bringing scale and simplicity
to the application of brain-inspired clinical algorithms to healthcare.
Their platform is built on a comprehensive and constantly growing
network of medical knowledge that powers their applications. Further,
the sheer amount of unprocessed data in healthcare is hindering patient
centered care. Their natural language processing taps into this data with
a deep understanding of clinical context and uses machine learning to
provide a profile of each patient’s risk (severity of disease and potential
adverse events, like a hospital readmission) that could not be generated
before. This enables true patient centered precision care. CloudMedx
combines the power of machine learning and big data analytics to
generate real-time health insights and improve patient outcomes
for chronic conditions that are responsible for as much as 90% of
healthcare costs such as congestive heart failure, stroke, hypertension,
COPD, diabetes, etc.
General :40: NLP, ML for healthcare
Category : ML,
Data Analysis,
NLP,
Neuroscience,
Predictive Analysis
Capital : $4.2M
Seed : $4.2M
SeriesA:
SeriesB:
Monetize : Providing software to hospitals
Founder: Tashfeen Suleman
Name : CLOUDMEDX 2014〜
HQ: Polo Alto
Employee: 11-50
Source : http://www.cloudmedxhealth.com/
Features :
• Investor : Y Combinator
• real-time health insights and improve
patient outcomes
Market : Healthcare

59
Zebra Medical Vision is building a medical imaging insights platform.
The company provides a platform that offers a cloud-based, fully
hosted research and development environment including access
to large datasets of structured, de-identified studies, storage, GPU
computing power and support for a multitude of research tools.
The solution also enables research groups to collaborate and
create joint tools.
General :41: Image recognition for health
Category : Health diagnosis,
Image recognition,
SaaS,
Capital : $20M
Seed : $8M
SeriesA:
SeriesB:
Monetize : providing software to hospitals
Founder: Elad Benjamin
Name : zebra 2014〜
HQ: Israel
Employee: 11-50
Source : https://www.zebra-med.com/
Features :
• GPU computing
• Automated, Accurate & Timely medical
image diagnosis
• Data driven healthcare
• constantly growing Analytics Platform
• he largest, open, clinical research
platform globally
• 1100↑ hospitals
Market : Healthcare

60
Enlitic, Inc. is a deep learning company dedicated to improving
healthcare diagnostics. Enlitic’s algorithms were engineered from the
ground up by a multidisciplinary team of renowned data scientists,
machine learning practitioners and medical experts in order to provide
faster, and more accurate medical diagnoses. Enlitic’s technology
analyzes and learns from vast quantities of unstructured medical data,
including radiology and pathology images, laboratory results, genomics,
patient histories and electronic health records. Using millions of records,
Enlitic’s Deep Learning technology can assist radiologists by improving
accuracy, reducing costs, and facilitating early detection in order to
improve outcomes.
General :42: DL for healthcare
Category : DL,
Healthcare diagnostics,
Capital : $15M
Seed : $5M
SeriesA: $10M
SeriesB:
Monetize : providing DL services
Founder: Sally Daub
Name : enlitic2014〜
HQ: San Francisco
Employee: 11-50
Source : https://www.enlitic.com/index.html
Features :
• faster, and more accurate medical diagnoses
• reducing costs, and facilitating early detection
• Creating data driven medicine using deep
learning
• up to 10,000 times faster than the average
radiologist.
Market : Healthcare

61
twoXAR is a software-driven drug discovery company. The company
leverages its computational platform to identify promising drug
candidates, de-risks the opportunities through preclinical studies, and
progresses drug candidates to the clinic through industry partnerships.
The platform has been applied to more than 80 diseases to date. In
collaboration with leading research institutions including Stanford,
University of Chicago, and Mt. Sinai Hospital, twoXAR has uncovered
promising new medicines for diseases such as arthritis, multiple
sclerosis,
and cancer.
General :43: ML for healthcare
Category : Pharmaceutical,
Biotechnology,
ML
Big Data,
Capital : $4.3M
Seed : $3.4M
SeriesA:
SeriesB:
Rounds: 2 rounds from 3investors
Monetize : Providing software for drug
Founder: Andrew A. Radin
Name : twoXAR 2014〜
HQ: Polo Alto
Employee: 11-50
Source : http://www.twoxar.com/
Features :
• intelligence-driven drug discovery company.
• Fast, scalable, unbiased, comprehensive,
agnostic.
• Partners : Stanford, MIT.
• Improving health through computation.Market : Healthcare

62
Based on the world’s most professional and exponentially increasing
holographic health data, they will provide individualized health analysis
and prediction of health index through the most advanced data mining
and machine analysis technologies. Together with the world’s leading
partners, they plan to observe, study, guide and take care of one’s health
from the beginning of one’s life. Multiple companies have established
collaboration and/or cooperation with us, including research institutions,
pharmaceutical factories, medical examination centers, hospitals,
insurance companies and health management companies, etc.
General :
44: Data Science for personalize
health
Category : Health Care,
Biotechnology,
Big data
Data Analysis
Capital : $199.48M
Seed :
SeriesA:
SeriesB:
Monetize : ???
Founder: Jun Wang
Name :
HQ: Shenzhen Chine
Employee: ???
Source : https://www.icarbonx.com/en/index.html
Features :
• O2O service
• holographic health data
• Personalization
• Unicorn in China
• Providing individualized health analysis and prediction of health
index
• the first and most comprehensive collection platform of health
data from millions of individuals
Market : Healthcare

63
Atomwise uses artificial intelligence to discover new potential medicines.
Atomwise built the first deep neural network for structure-based drug
design. Atomwise is helping researchers tackle chronic diseases such as
cancer, multiple sclerosis, and diabetes; neglected global diseases such as
Ebola and malaria; resurgent diseases such as antibiotic-resistant germs;
and bioterror threats such as botulinum neurotoxin. Atomwise trains deep
3D convolutional neural networks that autonomously learn spatial and
chemical features, and predict which molecules are likely to be effective.
The neural networks are applied throughout the drug discovery pipeline to
optimize the initial leads into potent medicines and adjust them to avoid
toxicity problems. Atomwise can analyze millions of molecules per day,
orders of magnitude faster than other physical testing technologies, and
helping find cures months or even years faster.
General :45: ML for drug
Category : Drug Discovery,
ML
Capital : $6.35M
Seed : $6.35M
SeriesA:
SeriesB:
Monetize : Discovering potential medicines
Founder: Abraham Heifets
Name : Atomwise 2012〜
HQ: San Francisco
Employee: 1-10
Source : http://www.atomwise.com/
Features :
• Partner : Merck, and IBM.
• artificial intelligence for discover new potential medicines.
• the first deep neural network for structure-based drug
design.
• Investor: Y Combinator
Market : Medical

64
Founded in 2015, Deep Genomics builds computational systems
that will improve how they diagnose, treat, and understand disease.
A key obstacle to realizing the benefits promised by routine genome
sequencing is the difficulty connecting individual genetic alterations
to physiological consequences that impact health. Deep Genomics is
working to close this gap. Deep Genomics’ technology emerged from
more than a decade of academic research that brought together the
fields of machine learning and genome biology. Their mission is to
develop an integrated computational system that can learn, predict and
interpret how changes in DNA – whether natural or therapeutic – alter
crucial cellular processes. They develop new machine learning methods
that can find patterns in massive datasets and infer computer models of
how cells read the genome and generate biomolecules. In this way, their
unique technology provides a causal interpretation for genetic variation
that is applicable to any variant, and any disease
General :46: ML for genomics
Category : DL,
ML,
Genome biology,
Capital : $3.7M
Seed : $3.7M
SeriesA:
SeriesB:
Monetize : Providing an integrated system
Founder: Brendan Frey
Name : deep genomics 2015〜
HQ: Toronto
Employee: 11-50
Source : https://www.deepgenomics.com/
Features :
• improve how they diagnose, treat, and understand disease.
• building an integrated computational system, the DG
Engine, which can learn, predict and interpret how genetic
variation, whether natural or therapeutic, alters crucial
cellular processes in the context of disease.
Market : Medical

65
babylon is a personal healthcare service that lives in your smartphone
or tablet. It’s easy to use, available whenever you need it and available
for everyone to use. It lets people arrange to see their lovely doctors
within minutes, chat to them face-to-face on their mobile to find out
what’s wrong, and then get back on track with sound advice. At babylon,
they’re on a mission to make healthier, happier people. So they’ve
created a bunch of features for the app to do just that. You can check
any symptom and ask all the questions you can think of using their chat
feature, send us questions for a speedy response and order test kits you
can do at home. They’re changing the way healthcare gets done.
Category : Chatbot,
Personalization,
NLP
Capital : $85M
Seed :
SeriesA: $60M
SeriesB: $20M
Monetize : Application charge
Founder: Ali Parsa
Name : babylon 2013〜
HQ: London
Employee: 50-100
Source : https://www.babylonhealth.com/pricing
Features :
• Personal healthcare service.
• It lets people arrange to see their lovely doctors
within minutes, chat to them face-to-face on their mobile to find out
what’s wrong.
• Health advice without going to hospital.
• Cheap £5 for month £39 for an appointmentMarket : Healthcare

66
Despite the huge growth of knowledge, scientific discovery has
not changed for 50 years. It’s impossible for humans alone to process all
of the information potentially available to advance scientific research - a
new scientific paper is published every 30 seconds, there are 10,000
updates to PubMed every day. Consequently, only a small fraction of
globally generated scientific information can form ‘useable’ knowledge.
BenevolentAI applies AI and deep learning techniques to enable the
analysis of vast quantities of complex scientific information. The Company
is changing the way knowledge is created by producing an enormous
structured, curated and qualified proprietary ‘data lake’ of dynamic usable
knowledge that can be applied for real world use in conjunction with
human experts. The Company’s first application of AI was in bioscience
to accelerate drug discovery. BenevolentAI is now expanding into other
large global scientific industries such a veterinary medicine, aggrotech,
nutraceuticals and materials science.
General :48: DL for madicine
Category : DL,
Neuroscience,
Augmented human intelligence,
Capital : $100M
Seed :
SeriesA:
SeriesB:
Monetize : Discovering new medicine
Founder: Jerome Pesenti
Name : BenevolentAI 2013〜
HQ: London
Employee: 51-100
Source : http://benevolent.ai/
Features :
• Deep learning techniques to enable the analysis of vast quantities of complex scientific
information.
• Bioscience to accelerate drug discovery, a veterinary medicine, aggrotech,
nutraceuticals and materials science.
Market : Medicine

67
Lunit is an AI-centric company and develops a visual perception
technology that interprets medical images and visualizes abnormal
regions based on its own data-driven criteria. The company gained
international attention after achieving the highest rank among startup
teams in the ImageNet Large-scale Visual Recognition Challenge
(ILSVRC) 2015. Based on the expertise in deep learning, Lunit has been
working on abnormality detection in chest x-ray, mammography as
well as automatic grading of breast histopathology slides. The high
level of Lunit’s technology has been well demonstrated, presented 4
scientific abstracts in Radiological Society of North America (RSNA)
2016 and won the first place in the Tumor Proliferation Assessment
Challenge (TUPAC) 2016 ahead of IBM and Microsoft. Lunit envisions
a constructive partnership between physicians and technology in
becoming “better together” faced with challenges in accurate diagnoses
of diseases.
Category : DL,
ML,
Health Diagnostics,
Image recognition
Capital : $5.46M
Seed :
SeriesA: $2M
SeriesB:
Monetize :developing advanced software
for medical data analysis
Founder: Anthony Paek
Name : Lunit 2013〜
HQ: Seoul
Employee: 11-50
Source :
Features :
• visual perception technology
• Investor: SoftBank
• help physicians make accurate, consistent, and
efficient clinical decisions, not limited to diagnoses,
through the data-driven imaging biomarker technology.
Market :

69
Voice calls are the enterprise’s most important data stream. They
represent 68% of customer contact, versus just 21% for email and chat.
They are how companies sell to customers and service their needs.
But this data — insights from the most critical customer conversations
— is not being captured, analyzed, or leveraged to grow and improve
business. TalkIQ has built a proprietary speech recognition and AI engine
for enterprise voice calls which is 2X more accurate than Watson and
3X more accurate than Google on these conversations. TalkIQ enables
sales and support teams to, for the first time, take a scientific approach
to understanding and optimizing key moments across their processes,
including recognizing purchase intent, handling objections, responding to
competitors, pricing, building rapport, and closing. As a result, companies
win more deals, retain more accounts, and improve their marketing and
product strategies to drive significant improvements against their most
important KPIs.
General :50: Voice recognition
Category : DL,
Speech recognition,
Predictive analysis
Capital : ???
Seed :
SeriesA:
SeriesB:
Rounds:
Monetize : providing speech recognition software
Founder: Dan O'Connell
Name : TalkIQ
HQ: San Francisco
Employee: ???
Source : https://www.talkiq.com/
Features :
• Voice recognition
• Delivering critical insights about the customers to
sales, marketing, account management, and
support teams
• Focus on customer conversation
Market : Customer support

70
Deepgram uses deep learning to mine your recorded speech
data for business insights. Companies only analyze 2% of their audio
data.
Deepgram does all of it. Predict churn, CSAT, NPS, conversion,
and search your data like you’re Google.
Category : Voice recognition
Capital : $1.92M
Seed :
SeriesA:
SeriesB:
Monetize : voice research
Founder: Scott Stephenson
Name : Deepgram 2015〜
HQ: San Francisco
Employee: 1-10
Source : https://www.deepgram.com/
Features :
• Focus on keyword spotting and AI classification for
phone support and legal discovery.
• Investor : Y Combinator
• searching keyword
• Use case : call center, eDiscovery, Media
Market : media, customer support

71
Persado’s cognitive content platform generates language that inspires
action. Powered by focused AI technologies, the platform arms Fortune
500 companies and other organizations with “smart content” that
maximizes engagement with any audience, for every touchpoint, at
scale,
while delivering unique insight into the specific triggers that drive action.
General :52: Cognitive computing for ad
Category : Cognitive computing,
Marketing,
Contents creator,
Advertisement
Capital : $66M
Seed :
SeriesA: $15M
SeriesB: $21M
SeriesC: $30M
Monetize : providing marketing solution
Founder: Alex Vratskides
Name : Persado 2012〜
HQ: New York
Employee: 101-250
Source : https://persado.com/
Features :
• “smart content” that maximizes the efficacy of
communication with any audience at scale.
• an average uplift of 49.5% in conversions across
marketing campaigns.
• Persado Go leverages a smart machine to analyze more
than 40 ,000,000,000 digital communication interactions.
• Persado’s cognitive content platform generates language
that inspires
action.
Market : Advertisement

72
Appier is a technology company that makes it easy for businesses to
use artificial intelligence to grow and succeed in a cross screen era.
Appier is formed by a passionate team of computer scientists and
engineers with experience in AI, data analysis, distributed systems, and
marketing. Their colleagues come from Google, Intel, Yahoo, as well
as renowned AI research groups in Harvard University and Stanford
University. Headquartered in Taipei, Appier serves more than 500
global brands and agencies from offices in eleven markets across Asia,
including Taipei, Singapore, Tokyo, Sydney, Ho Chi Minh City, Manila,
Hong Kong, Mumbai, New Delhi, Jakarta and Seoul.
General :53: ML for ad
Category : Analytics,
Personalization,
ML,
Marketing,
Ad
Capital : $81.5M
Seed :
SeriesA: $6M
SeriesB: $42M
SeriesC: $33M
Monetize : Providing ad solutions
Founder: Chih-Han Yu
Name : appier 2012〜
HQ: Taipei
Employee: 101-250
Source : http://www.appier.com/en/index.html
Features :
• Investors : SoftBank, LINE, Sequoia, etc
• Personalized ad
• provide artificial intelligence (AI) platforms to help
enterprises solve their most challenging business
problems, spanning across Marketing and Data
intelligence.
Market : EC, Gaming, Building a brand

73
Chorus helps your team make decisions using the insights you’d get
if you were sitting in on every sales or customer success call. They
founded Chorus to understand what influences conversation outcomes,
and make it easy to learn from and influence the thousands of
conversations your team has. Today, almost all of those conversations
and the insights they contain are forgotten the second they end,
except for the few notes captured in your CRM. They’re changing that.
They are a tight-knit team of world-class scientists, engineers and
product designers, and are working with a wide variety of data-driven
public and high-growth companies. They’re passionate about voices,
language, technology and results, and can’t wait to find the moments in
conversations that matter to you and your team.
General :54: Voice recognition for sales
Category : Voice recognition,
Big Data,
ML
Capital : $22.3M
Seed :
SeriesA: $16M
SeriesB:
Monetize : providing conversation intelligence for sales teams.
Founder: Roy Raanani
Name : Chorus 2015〜
HQ: San Francisco
Employee: 11-50
Source : https://www.chorus.ai/
Features :
• Automatically record, transcribe and analyze meetings in real-time. Gain
critical insight into your sales opportunities and meeting performance.
• understanding what influences conversation outcomes,
and make it easy to learn from and influence the thousands of
conversations your team has.
• Improving the skills of sales people and a manager's ability to manage
based on what is proven to impact the outcomes of sales conversations.
Market : CRM

74
Since its founding in 2004, InsideSales.com has developed a robust
platform that uses technology backed by the core ingredients of real AI
(big data, machine learning and predictive analytics, made actionable
with an application layer) to solve the who, what, where, when and how of
sales. As more and more of the tech industry’s titans enter the artificial
intelligence (AI) market, this AI fueled sales acceleration platform positions
InsideSales at the forefront of this wave. InsideSales.com has received
numerous accolades for its technology, including being named to the
CNBC Disruptor 50 and Forbes Cloud 100 lists, and earning recognition as
one of the fastest growing companies, according to Inc. InsideSales.com
enterprise customers include ADP, Microsoft and Groupon.
General :55: DL for sales
Category : ML,
Prediction,
Self learning
Capital : $251.2M
Seed :
SeriesA: $4M
SeriesB: $36.55M
SeriesC: $100M
SeriesD: $60M
Monetize : Providing CRM services
Founder: David Elkington
Name : Insidesales.com 2004〜
HQ: Provo
Employee: 500〜1000
Source : https://www.insidesales.com/
Features :
• InsideSales.com offers sales acceleration
platform built on a predictive and prescriptive
self-learning engine.
• comprehensive sales acceleration platform.
• Self communication, gamification, email and web
tracking, predictive forecasting, etc
Market : CRM

75
Drawbridge is the leading anonymized digital identity company, building
patented cross-device technology that fundamentally changes the way
brands connect with people. The Drawbridge Connected Consumer
Graph® includes more than one billion consumers across more than
three billion devices, and verified to be 97.3% precise. Brands can work
with Drawbridge in three ways: by licensing the Drawbridge Connected
Consumer Graph for cross-device data applications; managing crossdevice
ad campaigns in real-time using the Drawbridge Cross-Device
Platform; or working with Drawbridge to execute cross-device digital
advertising campaigns. The company is headquartered in Silicon Valley, is
backed by Sequoia Capital, Kleiner Perkins Caufield Byers, and Northgate
Capital, and has been named to the Inc. 5000 annual ranking of the
fastest-growing companies in America for the past two years.
General :56: ML for ad
Category : SaaS,
Personalization,
Ad,
Identity Management
Capital : $45.5M
Seed :
SeriesA: $6.5M
SeriesB: $14M
SeriesC: $25M
Monetize : Providing software which connect
brand and consumers
Founder: Kamakshi Sivaramakrishnan
Name : drawbridge 2010〜
HQ: San Mateo
Employee: 100〜250
Source : https://drawbridge.com/
Features :
• Anonymized digital identity
• Investor : Sequpia
• It enables brands to have seamless conversations with consumers.
• The Drawbridge Connected Consumer Graph® includes more than one
billion consumers across more than three billion devices, and verified to be
97.3% precise.
Market : Ad

76
DigitalGenius brings practical applications of deep learning and artificial
intelligence into customer service operations of leading companies. At
its core are deep learning algorithms, which are trained on historical
customer service data and integrated directly into the contact center’s
existing software. Already deployed with industry innovators like
KLM Royal Dutch Airlines, Unilever, and HSBC, the product delivers
value through two main functions: Predictive Case Intelligence: using
machine learning to predict and automatically pre-fill all case metadata
around an incoming customer service message. Improving
accuracy and significantly reducing average handling time. Human+AI
Question Answering: a deep learning algorithm trained on historical
customer service logs suggests and automates answers to customer
questions over email, live chat, social media, mobile messaging and
SMS. DigitalGenius has built a scalable deep-learning product for
the customer service industry, leveraging and creating cutting edge
research, to transform the customer service function inside businesses.
Category : Personalization,
DL,
NLP
Capital : $7.35M
Seed : $4.1M
SeriesA:
SeriesB:
Monetize : chatbot
Founder: Dmitry Aksenov
Name : DigitalGenius 2013〜
HQ: London
Employee: 51-100
Source : https://www.digitalgenius.com/
Features :
• deep learning and artificial intelligence into customer service
operations
• Predictive Case Intelligence: using machine learning to predict
and automatically pre-fill all case metadata
• Customer Support: Q&A
Market : Customer support

77
All of your users are different. Some are new, some will
never buy, while others are always looking to purchase more.
Retention Science built Artificial Intelligence (Cortex) to market
to each person in a relevant way that coincides with where
they are in their buying lifecycle.
General :58: SaaS
Category : Personalization,
CRM,
Marketing,
Prediction
Capital : $10.25M
Seed : $2.5M
SeriesA: $7M
SeriesB:
Monetize : Providing CRM tools
Founder: Jerry Jao
Name : Retention Science 2011〜
HQ: Santa Monica
Employee: 51-100
Source : https://www.retentionscience.com/#
Features :
• Target, engage and retain the customers.
• The data driven, SaaS-based Retention
Marketing platform predicts customer behavior
and delivers targeted multi-channel
communications
Market : Sales

79
Cylance is a cybersecurity products and services company focusing
on stopping tomorrow’s attacks today. Founded in 2012 by ex-McAfee
Global CTO Stuart McClure and ex-McAfee Chief Scientist Ryan Permeh,
Cylance was created to solve the malware problem once and for all.
Their flagship product, CylancePROTECT®, is the world’s first
nextgeneration antivirus built on artificial intelligence and machine
Learning. Named the SC Magazine Award winner for “Best
Emerging Technology” in 2015, CylancePROTECT offers exponentially
improved prevention capabilities when compared to other endpoint
security solutions. For a demo of CylancePROTECT, visit us at
cylance.com
General :59: ML for security
Category : ML,
Security
Capital : $177M
Seed :
SeriesA: $15M
SeriesB: $20M
SeriesC: $42M
SeriesD: $100M
Monetize : Providing service and consultant
Founder: Stuart McClure
Name : Cylance 2012〜
HQ: Irvin
Employee: 501-1000
Source : https://www.cylance.com/en_us/home.html
Features :
• global provider of cybersecurity products
• Prevent Cyberattacks with Artificial Intelligence
• Many product, and many services
Market : Cyber security

80
Sift Science provides real-time machine learning fraud prevention
solutions for online businesses across the globe. Its machine learning
software automatically learns and detects fraudulent behavioral
patterns, alerting businesses before they or their customers are
defrauded. Beyond this, the company has also launched a new
set of products designed to detect and mitigate additional types
of fraud and abuse, including: account abuse, content abuse, and
promo abuse.
Category : ML,
Fraud detection,
Security,
Big data
Capital : $53.6M
Seed : $1.6M
SeriesA: $4M
SeriesB: $18M
SeriesC: $30M
Monetize : $1000〜$10000 per a month
Founder: Jason Tan
Name : sift science 2011〜
HQ: San Francisco
Employee: 51-100
Source : https://siftscience.com/
Features :
• detect fraud and increase positive user experience.
• machine learning platform designed to secure trust,
reduce fraud, and grow the revenue.
• Payment fraud, account takeover, content abuse,
account abuse, promo abuse
Market : Security

81
A global leader and highly awarded cognitive computing analytics
company, SparkCognition is successfully deploying cutting-edge
Machine Learning and AI algorithms to provide intelligence to uncover
trends, anomalies, and cyber-physical threats while automatically
investigating and proposing solutions in IoT and network environments.
SparkCognition combines data from various sources, applies machine
learning to build automated models, and uses them to develop deep
insights into underlying performance, optimization, and security. The
company’s technology is capable of harnessing real time infrastructure
data and learning from it continuously, allowing for more accurate risk
mitigation and prevention policies to intervene in and avert disasters.
The company’s cybersecurity solutions analyze structured and
unstructured data and natural language sources to identify potential
failures or attacks in the IoT environment. The cognitive platform
continuously learns from data and derives automated insights to thwart
emerging issues.
Category : Cyber security,
ML,
IoT
Capital : $38.87M
Seed :
SeriesA: $370K
SeriesB: $38M
Monetize : Providing 3 security services
Founder: Amir Husain
Name : sparkcognition 2013〜
HQ: Austin
Employee: 11-50
Source : https://sparkcognition.com/
Features :
• the world’s first Cognitive Security Analytics
company.
• Applying Machine Learning & AI to Cloud Security
and the Internet of Things.
Market : Security

82
Deep Instinct is the first company to apply deep learning to cybersecurity.
Deep learning is inspired by the brain’s ability to learn. Once a brain learns
to identify an object, its identification becomes second nature. Similarly, as
Deep Instinct’s artificial brain learns to detect any type of cyber threat, its
prediction capabilities become instinctive. As a result, zero-day and APT
attacks are detected and prevented in real-time with unmatched accuracy.
Deep Instinct brings a completely new approach to cybersecurity that is
proactive and predictive. Deep Instinct provides comprehensive defense
that is designed to protect against the most evasive unknown malware in
real-time, across an organization’s endpoints, servers, and mobile devices.
Deep learning’s capabilities of identifying malware from any data source
results in comprehensive protection on any device, any platform, and
operating system.
General :62: DL for security
Category : DL,
Data Training,
Prediction
Capital : $32M↑
Seed :
SeriesA:
SeriesB: $32M
Rounds: ???
Monetize : security solutions
Founder: Guy Caspi
Name : deepinstinct 2014〜
HQ: Israel
Employee: ???
Source : https://www.deepinstinct.com/
Features :
• offering unmatched zero-day attack protection.
• By applying deep learning technology to cybersecurity,
enterprises can gain unmatched protection against
unknown and evasive cyber-attacks from any source.
Market : Security

83
Shift Technology provides insurance companies with a SaaS solution
designed to improve and scale fraud detection. The solution, which
can be rapidly implemented in as little as four months, seamlessly
integrates with the client’s existing operational processes and technical
context. Their Data Scientist team creates tailored algorithms designed
to reproduce an investigator’s deducting reasoning. Once the tool is fed
with client claims, their customized solution aggregates and analyzes
the data. The client can see results by logging into an easy-to-read/
customized dashboard highlighting the most suspicious cases. Each
claim is tagged with the potential risk of fraud along clear insights on
what makes the claim suspect. While there are many existing fraud
detection tools that can provide the “where” and the “when” Shift helps
the fraud handler determine the “why” and the “how” and can identify
not only the policyholder, but also service providers and full networks of
actors that could be part of the scam.
General :63: ML for fraud
Category : Insurance,
Big Data
Data Analysis
Capital : $11.8 M
Seed : $1.8M
SeriesA: $10M
SeriesB:
Rounds:
Monetize : fraud detection service
Founder: Jeremy Jawish
Name : shift technology 2013〜
HQ: Paris
Employee: 11-50
Source : http://www.shift-technology.com/
Features :
• provides insurance companies with a SaaS solution
designed to improve and scale fraud detection.
• automatically detect networks of fraudsters in insurance and e-
commerce.
Market : Insurance

84
Named ‘Best Security Company of the Year’ in the Info Security Products
Guide 2016, Darktrace is one of the world’s leading cyber threat defense
companies. Its Enterprise Immune System technology detects and
responds to previously unidentified threats, powered by machine
learning and mathematics developed by specialists from the University
of Cambridge. Without using rules or signatures, Darktrace is uniquely
capable of understanding the ‘pattern of life’ of every device, user and
network within an organization, and defends against evolving threats
that bypass all other systems. Some of the world’s largest corporations
rely on Darktrace’s self-learning technology in sectors including energy
and utilities, financial services, telecommunications, healthcare,
manufacturing, retail and transportation. Darktrace is headquartered
in Cambridge, UK and San Francisco, with offices in Auckland, Boston,
Chicago, Dallas, London, Los Angeles, Milan, Mumbai, New York, Paris,
Seoul, Singapore, Sydney, Tokyo, Toronto and Washington D.C.
Category : ML,
Cyber security
Capital : $179.5M
Seed :
SeriesA: $18M
SeriesB: $22.5M
SeriesC: $64M
SeriesD: $75M
Monetize :
Founder: Nicole Eagan
Name : DARKTRACE 2013〜
HQ: Cambridge
Employee: 101-250
Source : https://www.darktrace.com/
Features :
• Investor : SoftBank
• self-learning platform to spot anomalous activity within the
enterprise, in sectors including energy and utilities, financial
services, telecommunications, retail and transportation.
Market : cyber security

86
UBTECH is a high-tech enterprise engaging in the R&D, manufacturing
and promotion of commercial and consumer robots around the world.
The first company in China dedicated to commercializing humanoid
robots, UBTECH invested in humanoid robots research in 2008, and,
in 2012, established its headquarters in Shenzhen, China. UBTECH’s
mission is to bring robots into every home, and truly integrate intelligent
robots into the daily life of everyone, creating a more intelligent and
human-friendly way of leisure life. UBTECH will do this with continuous
investment in R&D to keep the core competence and a dedicated robotic
hardware and software technology development with a top robotic
engineering team. They also aim to have the most intellectual patents
in the humanoid service robotic industry, including invention patents,
industrial design patents, and practical patents. UBTECH will also
maintain its own manufacturing center and supply chain.
General :65: Robotics
Category : Robotics,
Consumer Electronics
Capital : $120M
Seed :
SeriesA: $20M
SeriesB: $100M
Monetize : Providing humanoid robot
Founder: James Chow
Name : UBTECH 2012〜
HQ: Shenzhen
Employee: 501-
Source : http://www.en.ubtrobot.com/
Features :
• R&D, manufacturing and promotion of commercial and consumer robots
• Humanoid robot
Market : leisure

87
Anki has a dream to bring artificial intelligence and consumer robotics
into everyday life. Anki’s cornerstone product is Anki Overdrive, based on
technology that brings together video games and physical toys. Using a
smartphone, the user can race a real toy car around Anki’s track, challenge
friends, or play against other cars controlled by Anki’s AI. As in a video
game, the cars adapt to their environment and surroundings, are fully
customizable through the app, and improve their performance with usage.
Category : ML,
Robotics,
Consumer electronics
Capital : $157M
Seed :
SeriesB: $50M
SeriesC: $55M
Monetize : consumer robots
Founder: Boris Sofman
Name : anki 2010〜
HQ: San Francisco
Employee: 51-100
Source : https://www.anki.com/en-us
Features :
• Anki Overdrive, based on
technology that brings together video games and physical toys.
• Investors: JPMorgan, Andreessen Horowitz
Market : leisure

88
Rokid features advanced artificial intelligence and deep learning that
enrich life by proactively delivering information, providing entertainment,
and performing household chores via voice and visual interactions.
Rokid is not just another high tech gadget, but a resourceful family
companion in smart homes. In addition to its sharp, modern design, it
embodies a warm and unique personality, with intuitive conversational
abilities and recognition of individual family members — making it
beyond a robotic device. Rokid emphasizes premium quality in every
facet of the build from software and hardware to industrial design and
manufacturing. With their full-stack technologies, developed in-house,
Rokid’s industry-leading performance is based on the company’s
proprietary software and hardware designs.
DL,
Consumer device
Capital : $50M↑
Seed :
SeriesA:
SeriesB: $50M
Monetize : B2C providing robots
Founder: Mingming Zhu
Name : Rokid 2014〜
HQ: Hangzhou
Employee: 51-100
Source : https://www.rokid.com/
Features :
• Smart home device
• Modern design
• Team: over 15 Ph.D.’s and more than 30 master’s holders.
• artificial intelligence, robotics, software, and hardware from
global brands including Alibaba, Samsung, Foxconn, Sony,
Nokia, and Google.
Market : Consumer device

89
Delivery is a huge and growing market - as it continues to grow
autonomy becomes increasingly essential. Dispatch is making delivery
smart by creating a platform for local delivery powered by a fleet of
autonomous vehicles designed for sidewalks and pedestrian spaces.
Dispatch’s first autonomous vehicle, nicknamed Carry, is designed to
deliver. The vehicle is small enough to navigate sidewalks, but large
enough to carry multiple packages. It operates in pedestrian areas and
travels no faster than a brisk walking pace, blending smoothly with
pedestrian traffic. Carry provides real time notifications throughout it’s
journey. Upon arrival, users receive a code to unlock their compartment
and grab their items. Then Carry is off to its next delivery
Category : DL,
Robotics,
Autonomous Vehicle,
Delivery
Capital : $2M
Seed : $2M
SeriesA:
SeriesB:
Monetize : delivering service
Founder: Uriah Baalke
Name : dispatch 2015〜
HQ: San Francisco
Employee: 1-10
Source : http://dispatch.ai/
Features :
• Delivery smart by creating a platform for local delivery powered by a fleet
of autonomous vehicles.
• robotics and artificial intelligence from MIT, UPenn, USC, UIUC, and UC
• Berkeley.
• Investor : Andreessen Horowitz
Market : delivering

91
Cambridge, MA-based nuTonomy develops state-of-the-art software
systems for self-driving vehicles. The company was founded by two
world-renowned experts in robotics and intelligent vehicle technology,
Drs. Karl Iagnemma and Emilio Frazzoli of MIT. The nuTonomy system
will provide point-to-point mobility via large fleets of autonomous
vehicles; this includes software for autonomous vehicle navigation in
urban environments, smartphone-based ride hailing, fleet routing and
management, and controlling a vehicle remotely through teleoperation.
The company is currently conducting public trials of its autonomous
ride-hailing service in Singapore, and will soon begin testing its self-
driving vehicles on public roads in Boston.
General :69: ML for self driving
Category : Autonomous Vehicle,
DL,
ML
Capital : $19.6M
Seed : $3.6M
SeriesA: $16M
SeriesB:
Monetize : self driving software
Founder: Karl Iagnemma
Name : nuTonomy
HQ: Cambridge
Employee: 51-100
Source : http://www.nutonomy.com/
Features :
• Focuse on inventing software for self-driving vehicles and autonomous mobile
robots.
• MIT spin off
• A Scalable, Full-stack Software Solution for Automated Driving.
Market : Vehicle

92
Drive.ai is a software company reimagining the fundamental relationship
between people and transportation. Founded in 2015 with a team
out of Stanford University’s Artificial Intelligence Lab, Drive.ai uses
sophisticated deep learning algorithms for a full-stack solution –
including perception and path planning, to control the vehicle – to power
the next era of transportation. Drive.ai’s product offering will consist
of a retrofitted self-driving kit for business fleets, with a long-term plan
to have their software integrated into new vehicles. This will include
sensors and a roof-mounted human-robot interaction outside the car,
all powered by deep learning software algorithms. The company’s initial
market approach will focus on proving the technology with route-based
vehicle fleets, in industries such as package delivery, ridesharing, and
public/private transit. Drive.ai is licensed to test autonomous vehicles in
the state of California.
Category : ML,
DL,
Autonomous Vehicle,
Capital : $62M
Seed :
SeriesA: $12M
SeriesB: $50M
Monetize : providing self-driving software
Founder: Brody Huval
Name : drive ai 2015〜
HQ: Mountain View
Employee: 50-100
Source : https://www.drive.ai/
Features :
• Stanford AI Lab
• Partner : Lift
Market : Vehicle

93
AImotive is a Budapest-based software company, developing a full-stack
software suite for fully autonomous self-driving cars. Established on
the idea that self-driving cars should mimic human behavior, AImotive’s
algorithms rely on cameras as primary sensors for accomplishing the
tasks of object recognition and classification, localization, decision
making, trajectory planning and vehicle control. Development and
operation processes follow the current automotive standards, providing
a hardware-agnostic, yet scalable solution. The software engine
components are aided by an extensive toolkit to accelerate the training
and verification, including calibration, data collection and augmented
data generation, semi-supervised annotation, and a real-time,
photorealistic simulation environment. Addressing the growing need
for hardware accelerators that are optimized specifically for artificial
intelligence, AImotive designs a power efficient, high performance neural
network hardware IP for automotive embedded solutions. The reference
design helps chip companies build the optimal hardware to support the
performance requirements of the AI-based software suite.
Category : ML,
DL,
Autonomous vehicle
Capital : $9.21
Seed :
SeriesA: $2.5M
SeriesB: €6M
Monetize : Providing self driving software
Founder: Laszlo Kishonti
Name : AIMOTIVE 2014〜
HQ: Budapest
Employee: 51-100
Source : https://aimotive.com/
Features :
• Hardware agnostic, full-stack software
• Toolkit that trains and verifies the AI with real-time simulations
• Power efficient, high-performance neural network hardware IP
for automotive embedded solutions
Market : Vehicle

94
NAUTO is a device, network and app that is an affordable way
to upgrade cars to get network and safety features previously
only available in high-end luxury cars. NAUTO’s system
includes an in-vehicle device that
collects and processes visual data in a smart and secure cloud,
which then produces valuable insights to help drivers operate
vehicles more efficiently, effectively and safely.
General :72: ML for camera
Category : ML,
DL,
Autonomous Vehicle,
Camera
Capital : $173.85M
Seed : $2.85M
SeriesA: $12M
SeriesB: $159M
Monetize : Providing AI camera
Founder: Stefan Heck
Name : NAUTO 2015〜
HQ: Polo Alto
Employee: 11-50
Source : https://www.nauto.com/
Features :
• Investor: SoftBank, Plug and Play, Toyota AI
• artificial intelligence-powered connected camera
network and smart cloud system
• real-time sensors and visual data help fleet managers
detect and understand the cause of accidents and
reduce false liability claims.
Market : Car

95
Founded in 2015, Nexar set a mission to rid the world of car crashes with
its vehicle-to-vehicle technology. The company has created a network of
connected Dashcam apps that record the drive and alerts you to potential
incidents ahead of time. In the event of a crash, the Nexar app can provide
drivers with evidence of events as they occurred to help them with their
insurance claim. Leveraging millions of crowdsourced road miles jointed
with sensor-fusion, deep-learning, map-layering and artificial intelligence
technologies Nexar provides a series of data products and services for the
Automotive, Insurance and Mapping industries. Nexar is a member of the
Berkeley DeepDrive Industry Consortium, a research alliance that develops
AI-based perception applications for the automotive industry.
General :73: DL for driving
Category : ML,
DL,
Sensor,
Camera
Capital : $14.5M
Seed :
SeriesA: $14.5M
SeriesB:
Monetize : providing real-time alert
Founder: Eran Shir
Name : nexar 2015〜
HQ: Tel Aviv
Employee:11-50
Source : https://www.getnexar.com/
Features :
• created a network of connected Dashcam apps that record the drive and alerts
you to potential incidents ahead of time
• vehicle-to-vehicle network.
• Leveraging connected smartphones and car cameras and sensors
• real-time alerts to prevent vehicle, cyclist and pedestrian collisions.
Market : car

96
Zoox is a robotics company founded by Tim Kentley-Klay and Jesse
Levinson. They’re developing fully-autonomous vehicles and the
supporting ecosystem required to bring this technology to market.
Sitting at the intersection of robotics, machine-learning, and design,
Zoox aims to provide the next generation of mobility-as-a-service
in urban environments. They believe the transition to self-driving
vehicles requires a combination of elegant vision and uncompromising
execution.
General :74: DL for Self driving car
Autonomous mobility,
EV
Capital : $290M
Seed : $40M
SeriesA: $250M
SeriesB:
Monetize : Mobility as a service
Founder:Tim Kentley-Klay
Name : Zoox 2014〜
HQ: Menlo park
Employee: 101-250
Source : http://zoox.com/
Features :
• developing a breakthrough, fully automated,
electric vehicle fleet and the supporting ecosystem
• Investor: SoftBank ?
Market : car

98
Clarifai is an artificial intelligence company that excels in visual
recognition, solving real-world problems for businesses and developers
alike. Founded in 2013 by Matthew Zeiler, a foremost expert in machine
learning, Clarifai has been a market leader since winning the top five places
at the ImageNet 2013 competition, and predicts more than 1.4 billion
concepts in images every month. Clarifai’s powerful visual recognition
technology is built on the most advanced machine learning systems and
made easily accessible by a clean API, empowering developers all over
the world to build a new generation of intelligent applications. Clarifai
builds products to make it easy, quick, and inexpensive for developers and
businesses to innovate with AI, go to market faster, and build better user
experiences. Clarifai also makes “teaching” AI just as accessible as they
make using AI, which is why their technology is the most customizable and
accurate solution in the market.
Category :DL,
Image recognition,
Capital : $40M
Seed :
SeriesA: $10M
SeriesB: $30M
Monetize : Providing APIs
Founder: Matthew Zeiler
Name : clarifai 2013〜
HQ: New York
Employee: 11-50
Source : https://clarifai.com/
Features :
• advanced image recognition systems for
customers to detect near-duplicates and visual
searches.
• predicts more than 1.4 billion
concepts in images every month
Market : Image, movie

99
Chronocam is developing a unique, bio-inspired and self-adapting
approach to the need for visual sensing and processing in autonomous
vehicles, connected devices, security and surveillance systems. Its
innovative vision sensors and systems replicate the functioning of the
human eye and address the limitations of conventional vision sensors
by enabling real time sensing of the relevant dynamic scene context and
acquiring only what is necessary. The result is that Chronocam’s vision
solutions set a new benchmark for computer vision performance with
unprecedented speed, dynamic range, sensor level video compression and
power efficiency, at the same time. Based in Paris, Chronocam is a venture
backed company with investors including 360 Capital, CEA Investissement,
iBionext, Intel Capital, Renault-Nissan Group, and Robert Bosch Venture
Capital. More information can be found at chronocam.com.
General :
76: Image recognition for
machines
Autonomous Vehicle,
DL,
Drone,
Sensor
Capital : $18.35M
Seed : €750K
SeriesA:
SeriesB: $15M
Monetize : Providing sensor and IL solutions
Founder: Luca Verre
Name : chronocam 2013〜
HQ: Paris
Employee: 11-50
Source : http://www.chronocam.com/
Features :
• bio-inspired computer vision solutions for
autonomous navigation and connected objects.
• machine vision sensors and systems for
applications in all fields of machine vision.Market : All field of machine vision

100
Orbital Insight works at the intersection of big data and the
commercialization of space and is the first mover in large-scale
Analysis of satellite and UAV imagery. The company has
developed algorithms to count and measure cars, roads, airplanes,
clouds, haze, freshwater lakes, agricultural fields, buildings, and oil
tanks to provide a big-picture understanding of the world quantitatively
grounded in observation.
General :77: Geospatial Analysis
Image recognition,
satellite
Capital : $78.7M
Seed :
SeriesA: $8.7M
SeriesB: $20M
SeriesC: $50M
Rounds: 4 rounds from13 investors
Monetize : providing geospatial analysis
Founder: James Crawford
Name : Orbital Insight 2013〜
HQ: Mountain View
Employee: 11-50
Source : https://orbitalinsight.com/industries/#slider-3
Features :
• a macroscope and finding truth and transparency
in the ever-expanding supply of satellite images.
• Visualizing
• Geospatial Analytics for an Interconnected World
Market :Finance, Energy, Insurance,
NGO, public

101
Deep learning has enabled large improvements in the accuracy and
robustness of computer vision systems, enabling revolutionary
applications such as intelligent security cameras and self-driving
cars. Traditionally, these improvements in accuracy and robustness
have come at a cost of high computational requirements, limiting
the applications that deep learning can benefit. Pilot AI Labs aims to
expand the applications that ing can benefit by significantly reducing the
compute requirements of these algorithms, with the goal of enabling
embedded applications without the need for custom silicon. Pilot AI
licenses its software to others, and counts several public multi-national
corporations as its customers. Pilot AI’s software will be deployed in
millions of devices by early 2017.
Category : ML,
Image recognition,
IoT
Capital :
Seed :
SeriesA:
SeriesB:
Monetize : licenses its software
Founder: Jonathan Su
Name : pilot.ai 2015〜
HQ: Redwood city
Employee: 11-50
Source : http://www.pilot.ai/
Features :
• Software-based deep learning computer vision
• Pilot AI’s software will be deployed in
millions of devices by early 2017.
Market : software IoT

102
Captricity is secure cloud software that transforms handwritten paper
forms into digital data with 99%+ percent accuracy. Captricity’s cloud
solution features unique crowd-guided deep learning technology that can
extract data from any source - paper documents, scans, faxes, emails, call
centers and web forms - and connect automatically to backend systems to
empower advanced analytics and eliminate the need for costly, ineffective
manual data entry processes. Captricity serves a broad range of markets,
including insurance, healthcare, government and non-profits.
General :79:
Category :
Capital :
Seed :
SeriesA:
SeriesB:
Rounds:
Monetize :
Founder:
Name :
HQ:
Employee:
Source :
Features :
• aaa
Market :

103
Given a photo, consumers want answers to questions like “What is
this product? Where can I buy it?”, “Show me where/how people are
using this product”, “Who in the world is posting about this product?”
GrokStyle provides these answers using innovations in deep learning
technology, developed by co-founders Dr. Sean Bell (CEO) and Prof.
Kavita Bala (Chief Scientist). GrokStyle is developing software for visual
search to enable instant recognition of an object. The techniques they
are developing can be applied broadly to domains like interior design,
apparel search, real estate search, product lookup, etc. The company’s
current focus is on interior product design. GrokStyle will provide
new capabilities to consumers and retailers to assist in matching
a consumer’s desired product with the correct or closest matching
product based a visual similarity.
General :
80: Image recognition of an
object
Category : DL,
Capital :
Seed :
SeriesA:
SeriesB:
Rounds:
Monetize : providing software
(recognition of object)
Founder: Sean Bell
Name : GROKSTYLE
HQ: San Francisco
Employee:11-50
Source : http://landing.grokstyle.com/
Features :
• software for visual search to enable instant
recognition of an object.
• can be applied broadly to domains like interior
design, apparel search, real estate search,
product lookup, etc.
Market : Furniture

105
MindMeld is a technology company based in San Francisco, California.
MindMeld’s Deep-Domain Conversational AI platform takes natural
language voice or text inputs and delivers a conversational UI at the
other end to any device of application. The conversational UI can
take the form of a chat assistant, a voice assistant, or a multi-modal
interface that switches seamlessly between touch, type and speech.
The assistant maintains ongoing dialog using these modalities to
either conduct search (e.g. for shopping) or answer questions (e.g. for
customer support). MindMeld’s language models are built on customers’
data sets, allowing for an advanced degree of functionality in proprietary
content domains — even across massive domains with billions of
permutations of queries. MindMeld’s customers and investors include
Google, Samsung, Uniqlo, Spotify, Intel, Telefonica, Liberty Global, IDG,
USAA, In-Q-Tel and others.
General :81: Conversational AI
Category : NLP,
ML,
Voice recognition,
Capital : $15.4M
Seed :
SeriesA: $13M
SeriesB:
Monetize : NLP and voice recognition software
Founder: Tim Tuttle
Name : MindMeld
HQ: San Francisco
Employee: 11-50
Source : https://www.mindmeld.com/
Features :
• Acquired by cisco $125M
• Advanced AI platform powering a new generation of
intelligent conversational interfaces.
• Partner: Intel, Sumsung, Spotify, Uniqulo
Market : Music, Retail, etc

106
Semantic Machines is a privately held Artificial Intelligence technology
developer with offices in Berkeley, California and Boston, Massachusetts.
Backed by $21M in venture capital from Bain Capital Ventures, General
Catalyst and others, the company is creating the fundamental AI
technology needed to teach computers to understand language,
comprehend context and interact naturally. The company plans to provide
its highly customizable AI platform technology to strategic partners.
General :82: Conversational AI
Category : NLP,
Voice recognition,
Capital : $21M↑
Seed :
SeriesA:
SeriesB:
Monetize : providing conversational AI
Founder: Daniel Roth
Name : semantic machines 2014〜
HQ: Newton
Employee:11-50
Source :
Features :
• Developing a new kind of mobile experience that will let people accomplish
things in an amazing new way.
• developing technology that goes beyond understanding commands, to
understanding conversations.
• Conversational AI interfaces
Market : EC, Travel, Search, etc

107
Maluuba is a Canadian deep-learning company helping machines to
think, reason and communicate with human-like intelligence. Their vision
is a world where intelligent machines work hand-in-hand with people
to bring about positive social and economic impacts. Their research
team is dedicated to tackling big challenges in machine intelligence.
With a focus on deep learning and reinforcement learning, they work
closely with industry and academic partners like the Montréal Institute
for Learning Algorithms (MILA) and McGill University. They share
their research findings through academic papers and datasets and
they present at AI conferences. They work with enterprise partners in
communications, customer experience, technology and professional
services, applying their research to help develop products and services
powered by natural language understanding. Maluuba has offices in
Montréal, a global hub for AI research, and in Waterloo, home to many of
Canada’s leading technology companies.
General :83: DL for machine training
Category : NLP,
ML,
DL,
Voice recognition
Capital : $11M
Seed : $2M
SeriesA: $9M
SeriesB:
Monetize : machine intelligence training
Founder: Sam Pasupalak
Name : maluuba 2011〜
HQ: Waterloo
Employee:11-50
Source : http://www.maluuba.com/
Features :
• Acquired by Microsoft
• company helping machines to
think, reason and communicate with human-like intelligence.
• Tackling reasoning, decision-making and communication in machines through
groundbreaking research
Market : ???

108
Mobvoi is an innovative AI company with in-house voice search
technologies: speech recognition, natural language understanding,
vertical search and proactive search. In October 2015, Mobvoi closed
series-C round financing led by Google Inc. This was Google’s first direct
investment in a Chinese company in the past six years. Since founding
in late 2012, the company has raised over $75 million with a valuation of
$300 million as of October 2015. Leveraging its voice search
technologies,
Mobvoi developed the smartwatch operating system Ticwear in late
2014
and launched Ticwatch, the online best-selling Android based
smartwatch
in China, in June 2015.
Semantic analysis,
Capital : $251.62M
Seed :
SeriesA: $1.62M
SeriesB: $10M
SeriesC: $60M
SeriesD: $180M
Monetize : Providing voice search service
Founder: Zhifei Li
Name : Mobvoi 2012〜
HQ: Beijing
Employee: 11-50
Source : http://www.chumenwenwen.com/en/site/index.html
Features :
• AI company with in-house voice search technologies:
speech recognition, natural language understanding,
vertical search and proactive search.
• The smartwatch operating system
• Investors: Google, SequoiaMarket : Mobile voice search

109
KITT.AI is a Seattle-based Natural Language Understanding startup
supported by the Allen Institute for Artificial Intelligence, Amazon Alexa
Fund, Founders’ Co-op and Madrona Venture Group. KITT.AI’s customizable
hotword detector and conversation engine ChatFlow bring always-on and
multi-turn dialogue capabilities to any voice or text based devices/bots.
General :85: NLP for chatbot
Category : NLP,
Capital :
Seed :
SeriesA:
SeriesB:
Monetize :
Founder: Kenji Sagae
Name : KITT AI 2014〜
HQ: Seattle
Employee: 1-10
Source : http://kitt.ai/
Features :
• Acquired by Baidu
• Robust Natural Language Understanding (NLU)
and an intuitive conversation engine
• Customizable Hotword Detection
Market : Chatbot

110
Snips is an SDK enabling anyone to create their own AI assistant, in a
single line of code. It was built with security and privacy in mind, and is the
first assistant to run fully on device, without the need for a server.
There are 41 people in the team, including 18 on machine learning
and 14 on engineering. All Founders are PhDs, and the leadership is
comprised of serial entrepreneurs in the Privacy and Mobile space. SDK
features NLP, natural language queries by voice or text, robust query
understanding using deep learning, recursive query solving, pre-trained
domains for multiple languages. It also uses context awareness and
privacy technology: contextual disambiguation of entities from location,
calendar, emails, and chats. And it runs fully on device, including neural
nets and is private by design: no data leaves the user’s device. It’s
available on mobile (iOS, Android); server and desktop (Java, Scala,
MacOS), and the IoT (TvOS, WatchOS, Android Things).
General :86: Voice recognition SDK
NLP,
Capital : $19.3M
Seed : $6.3M
SeriesA: $13M
SeriesB:
Monetize : Providing SDK
Founder: Rand Hindi
Name : snips 2013〜
HQ: Paris
Employee: 11-50
Source : https://snips.ai/
Features :
• SDK to create own AI assistant
• AI voice platform for connected devices.
• Can run without the need for a server or the
cloud.
• Investor: 500 startups
Market : voice recognition

111
Clara Labs manages your work calendar in a smarter, more efficient
way than a human is capable of. When you need to schedule a meeting
just CC “clara@yourcompany.com” and Clara will take over the email
dialogue, sending the calendar invitation on your behalf. Clara supports
hundreds of teams across the globe, from executives to sales orgs to
recruiters, saving thousands of hours a week in tedious back-and-forth.
Clara’s human-in-the-loop architecture maintains its conversational
warmth and intelligence, while dramatically lowering the cost of
receiving scheduling assistance. With Clara, your time is free to focus on
the work that matters.
General :87: NLP for task management
Category : Task Management,
NLP
Capital : $12M
Seed : $5M
SeriesA: $7M
SeriesB:
Monetize : Task Management
Founder: Maran Nelson
Name : clara 2014〜
HQ: San Francisco
Employee: 11-50
Source : https://www.claralabs.com/
Features :
• an automated system that handles meeting
coordination through emails and manages the
complexity of its users’ calendars.
• Investor: Sequoia
Market : Business operation

112
Automat is the world’s first AI powered Conversational Marketing
Platform. They enable companies to have personalized one-on-one
messaging conversations with their customers to drive meaningful
engagement that improves upon decades of static catalog-like website
and mobile app content. Automat’s Bot Creator authoring environment
lets marketing professionals, creatives, and developers collaborate to
build Conversational Software powered by artificial intelligence that
beats today’s one-size-fits-all sales funnels. Starting either from their
Bot Library of pre-existing marketing objective templates such as
Product Discovery, Influencer Marketing, Scheduling, Conversational
Ads, etc, or beginning from scratch to build a wholly original
conversational campaign, marketers can now reach mobile customers
where they spend the bulk of their time, inside popular messaging apps
like Messenger, Kik, WhatsApp, and WeChat. Riding on top of Automat’s
Conversation as a Service (CaaS) platform, marketers can harness the
power of Conversational Language Understanding (CLU) to recognize
what consumers are saying about their brand and products providing a
personalized one-on-one purchasing experience.
General :
88: Voice recognition for
marketing
Category : NLP,
ML,
Voice recognition
Capital : $10.9M
Seed : $2.6M
SeriesA: $8.3M
SeriesB:
Monetize :
Founder: Andy Mauro
Name : Automat 2016〜
HQ: Montréal
Employee: 11 - 50
Source : http://www.automat.ai/
Features :
• Conversational Marketing for Brands
• personalized one-on-one messaging conversations with their customers to drive meaningful
engagement
• , inside popular messaging apps like Messenger, Kik, WhatsApp, and WeChatMarket : Marketing

113
Founded in 2014, x.ai makes an artificial intelligence personal assistant
who schedules meetings for you. There’s no sign-in, no password, no
download. All you do is CC amy@x.ai into your email conversation, just
like you would a human personal assistant. Amy (or her twin brother
Andrew) then takes over the tedious email ping pong that comes along
with scheduling a meeting. They’re a hardcore technology company,
developing invisible software. They build their business sustainably
through passionate and loyal customers—and every single team
member, scientist or not, has a mission of delivering exceptional
customer service at all times. They’re backed by blue chip investors,
including IA Ventures, Firstmark, Two Sigma Ventures, SoftBank Capital,
DCM and Pritzker Group. Their team is located in New York City.
General :89: ML for Business Assistat
Category : ML,
Virtual Assistance
Capital : $44.3M
Seed : $2.1M
SeriesA: $9.2M
SeriesB: $33M
Monetize : Provide personal assistant tool
Founder: Dennis Mortensen
Name : X.ai 2014〜
HQ: New York
Employee: 51-100
Source : https://x.ai/
Features :
• Investor: SoftBank
• builds and maintains an artificial
intelligence powered personal
assistant that schedules
meetings for the business
customers.
Market : Business Assistant

115
DataRobot automates the process of building machine learning models.
The platform empowers users enterprise-wide to make smarter,
faster business decisions by delivering unmatched speed, accuracy,
and automation at scale. From the progressive business analysts or
statisticians to the applied data scientists - users from around the globe
are building and deploying accurate predictive models in a fraction of
the time it used to take. DataRobot addresses the critical shortage of
data scientists by changing the speed and economics of predictive
analytics. The platform uses massively parallel processing to train
and evaluate 1000’s of predictive models in R, Python, SparkML, H2O,
Tensorflow and other open source libraries. It searches through millions
of possible combinations of algorithms, pre-processing steps, features,
transformations and tuning parameters to deliver the best models for
a given dataset and prediction target. Watch the video “Presenting
DataRobot” datarobot.wistia.com/medias/cqkjuzsp0z
General :90: Automated ML
Category : SaaS,
ML,
Capital : $124M
Seed : $3.5M
SeriesA: $21M
SeriesB: $33M
SeriesC: $67M
Monetize : Provide predictive analysis platform
Founder: Jeremy Achin
Name : datarobot 2012〜
HQ: Boston
Employee: 101-250
Source : https://www.datarobot.com/
Features :
• Investor: Techstars, Plug and Play, Intel etc
• changing the speed and economics of predictive
analytics.
• predictive analytics platform to rapidly build and deploy
predictive models the cloud or an enterprise.
Market : B2B data science company

116
Trifacta, founded in 2012, significantly enhances the value of an
enterprise’s Big Data by enabling users to easily transform raw, complex
data into clean and structured formats for analysis. Leveraging decades
of work in human-computer interaction, scalable data management and
machine learning, Trifacta’s technology creates a partnership between
user and machine, with each side learning from the other and becoming
smarter with experience. Whether you’re trying to improve the efficiency of
an existing analysis process or utilize new sources of data for an analytics
initiative, Trifacta’s data wrangling solutions will empower you to do more
with data of all shapes and sizes.
General :91: Data Analysis
Analytics,
Capital : $76.3M
Seed :
SeriesA: $4.3M
SeriesB: $12M
SeriesC: $60M
Monetize : Providing data analysis platform
Founder: Adam Wilson
Name : Trifacta 2012〜
HQ: San Francisco
Employee: 101-250
Source : https://www.trifacta.com/
Features :
• create radical productivity for people who work with data.
• 70% Reduction in END-to-END reporting time.
• 50,000HRS saved from more efficient data
warnings
• 10X Faster customer on-boarding processMarket : Data analysis

117
RapidMiner, the industry’s #1 open source data science platform, is
disrupting the industry by empowering all organizations to put data
science behind every decision. Their visually-based software accelerates
the process of creating predictive analytics models and makes it
easy to get the results embedded in business operations. RapidMiner
also democratizes data science through its expert marketplace by
connecting its vast community of expert users with organizations
seeking to begin data science projects at a fraction of the cost of
existing solutions.
Category : ML,
Big Data,
Predictive analysis
Capital : $36M
Seed :
SeriesA: $5M
SeriesB: $15M
SeriesC: $16M
Monetize : B2B analytical software
Founder: Peter Lee
Name : rapidminer 2007〜
HQ: Boston
Employee: 51-100
Source : https://rapidminer.com/
Features :
• visually-based software
• creating predictive analytics models and
makes it easy to get the results embedded in
business operationsMarket : Data Analysis

118
Tamr delivers the clean, curated data critical for optimizing key
decisions. Tamr’s unique machine-drive plus human-guided solution
automates the mastering and organization of enterprise-wide data
(suppliers, customers, products, transactions) that enables previously
unattainable cost and revenue analytics. Tamr works with Global 2000
companies like Amgen, GE, GlaxoSmithKline, Thomson Reuters, and
Toyota to help fuel transformational analytics. Based in Cambridge,
Mass., Tamr was founded in 2013 by database industry veterans Andy
Palmer, Mike Stonebraker and Ihab Ilyas
Category : ML,,
Big Data,
Analysis
Capital : $41.2M
Seed :
SeriesA: $16M
SeriesB: $25M
Monetize : B2B analytical software
Founder: Andy Palmer
Name : Tamr 2012〜
HQ: Cambridge
Employee: 11-50
Source : https://www.tamr.com/
Features :
• data source connectivity and enrichment fast, cost-
effective, scalable and accessible to the entire
enterprise.
• building a commercial-grade solution designed to
tackle the challenge of connecting and enriching
diverse data
Market : Data Analysis

119
SigOpt is the optimization platform that amplifies your research. SigOpt
takes any research pipeline and tunes it, right in place. Their cloud-based
ensemble of optimization algorithms is proven and seamless to deploy,
and is used by globally recognized leaders within the insurance, credit
card, algorithmic trading and consumer packaged goods industries.
SigOpt was born out of the desire to make experts more efficient. While
co-founder Scott Clark was completing his PhD at Cornell he noticed
that often the final stage of research was a domain expert tweaking
what they had built via trial and error. After completing his PhD, Scott
developed MOE to solve this problem, and used it to optimize machine
learning models and A/B tests at Yelp. SigOpt was founded in 2014 to
bring this technology to every expert in every field.
General :94: ML
Category : SaaS,
ML
Capital : $8.72M
Seed : $2.2M
SeriesA: $6.6M
SeriesB:
Monetize : Providing the optimization platform
Founder: Scott Clark
Name : SIGOPT 2014〜
HQ: San Francisco
Employee: 1-10
Source : https://sigopt.com/
Features :
• Investor: Ycombinator, Stanford Uni
• seamless to deploy
• Improving ML 100× faster
Market : ML

120
Paxata is an Adaptive Data Preparation platform for the enterprise.
Paxata’s platform provides an interactive, analyst-centric data prep
experience powered by a unified set of technologies designed from
the ground up for data integration, data quality, semantic enrichment,
collaboration and governance. Information-driven organizations who
want to make data worth analyzing use Paxata to explore, clean, shape,
and combine all the data they need into rich AnswerSets which power ad
hoc, operational, predictive and packaged analytics. Paxata’s platform,
built on Apache Spark and optimized to run in Hadoop environments,
leverages distributed computing, machine learning and a dynamically
visual workspace that promotes transparent governance and ad hoc
collaboration. Paxata data prep, powered by IntelliFusion, is designed
to eliminate the need for coding, scripting and sampling. The solution is
available as a service, and can be deployed in AWS virtual private clouds or
within Hadoop environments at customer sites.
Category : Big Integration,
Capital : $61M
Seed :
SeriesA: $1.49M
SeriesB: $8M
SeriesC: $18M
SeriesD: $33.5M
Monetize : providing a platform for data analyst
Founder: Prakash Nanduri
Name : Paxata 2012〜
HQ: Redwood city
Employee: 51-100
Source : https://www.paxata.com/
Features :
• Adaptive Data Preparation platform for the enterprise.
• Built on Apache Spark and optimized to run in Hadoop
environments.
• Platform built for the analyst to turn raw data into ready data
for analytics.
Market : Data analytics

121
Context Relevant products solve some of the world’s toughest big data,
predictive, and behavioral challenges using Their machine learning
driven Automated Data Science platform—faster and more effectively
than any other solution. The Context Relevant machine learning platform
takes the best of open source infrastructure, such as Hadoop and Spark,
and ties it together with their proprietary Automated Data Science
engine and application environment. The result is a full-stack, production
ready platform that enables the rapid creation, testing, and deployment
of data science- and predictive analysis-driven intelligent applications.
Category : Data Analysis,
Predictive Analysis,
ML,
Capital : $57M
Seed : $2.8M
SeriesA: $7M
SeriesB: $33.5M
SeriesC: $12.7M
Monetize : Providing data security and
creaning service.
Founder: Joseph Polverari
Name : Versive 2012〜
HQ: Seattle
Employee: 11-50
Source : https://www.versive.com/
Features :
• Big data analytics
• Automatically explores complex combinations of
inputs
• Changed the name at 2015.
Market : Cyber security, Data analysis

122
Dataminr is a service that creates real-time, actionable breaking news
alerts from public social media activity. Dataminr’s powerful algorithms
instantly transform all publicly available Twitter data and other public
datasets into actionable news alerts that enable security, operations,
financial and communications professionals around the world to be
proactively alerted to must-know information as events unfold. Alerts are
delivered via desktop applications and workflow-integrated notifications.
Global corporations, financial firms, news organizations and the public
sector rely on Dataminr to know about breaking news early so they can
respond quickly to the incidents and disruptions that can impact their
people, assets, portfolios, and operations.
General :97: Predictive Analysis
Category : Data Analysis,
Security,
Financial service,
Social media
Capital : $183M
Seed :
SeriesA: $1.09M
SeriesB: $16.5M
SeriesC: $33.8M
SeriesD: $130M
Monetize : Providing APIs etc
Founder: Ted Bailey
Name : Dataminr 2009〜
HQ: New York
Employee: 101-250
Source : https://www.dataminr.com/
Features :
• real-time, actionable breaking news
alerts from public social media activity.
• develops modular desktop and API
products that provides custom signal
creation, integration of data sets and back-
testing services.
Market : Finance, security, public

123
CrowdFlower is the essential human-in-the-loop platform for data science
teams. CrowdFlower helps customers generate high quality customized
training data for their machine learning initiatives, or automate a business
process with easy-to-deploy models and integrated human-in-the-loop
workflows. The CrowdFlower platform supports a wide range of use cases
including self-driving cars, intelligent personal assistants, medical image
labeling, content categorization, customer support ticket classification,
social data insight, CRM data enrichment, product categorization, and
search relevance. Headquartered in San Francisco and backed by Canvas
Venture Fund, Trinity Ventures, and Microsoft Ventures, CrowdFlower
serves data science teams at Fortune 500 and fast-growing data-driven
organizations across a wide variety of industries.
Category : ML,
Enterprise software
Capital : $58M
Seed : $1.2M
SeriesA: $5M
SeriesB: $9.3M
SeriesC: $12.5M
SeriesD: $10M
Monetize : $1500/ month
Founder:Robin Bordoli
Name : crowdflower 2007〜
HQ: San Francisco
Employee: 51-100
Source : http://x-movies21.com/movie/420283/dolores.html
Features :
• essential human-in-the-loop platform for data science
teams.
• helps customers generate high quality customized
training data for their machine learning.Market : Data analysis

124
Logz.io is a log analysis platform that uses AI and and machine-learning
algorithms to find critical events in the volumes of information that
are now constantly generated in IT environments. Created by a Check
Point veteran and a former algorithm engineer for the Israeli military,
the enterprise-grade, cloud platform is built on top of the ELK Stack and
provides real-time access to data insights based on the collaborative
knowledge of system administrators, DevOps engineers, and developers
throughout the world. The ELK Stack — Elasticsearch, Logstash, and
Kibana — is the world’s most popular open-source log analytics software
stack
Category :ML,
Predictive Analysis,
Capital : $23.9M
Seed :
SeriesA: $6.7M
SeriesB: $16M
Monetize : Providing analytics tool
Founder: Tomer Levy
Name : logz.io 2014〜
HQ: Tel Aviv
Employee: 11-50
Source : https://logz.io/
Features :
• Cognitive insight
• Analysis platform that uses AI
and and machine-learning
algorithms to find critical events
Market : Developers, Engineers

125
Algorithmia helps developers, enterprises, and academics create, host,
distribute, and monetize intelligent microservices. Today, over 30,000
developers have access to a growing library of 2,500 algorithmic
microservices they can integrate into their applications through a
simple REST API. Algorithmia’s mission is to advance the development,
discovery, and accessibility of algorithmic intelligence. They believe
Artificial Intelligence should be available to any developer regardless
of language or technology stack. Today, Algorithmia provides two
major products: Algorithmia.com, a marketplace for microservices,
and CODEX, a platform for functions and AI models. CODEX helps
organizations centralize shared services, discover internal algorithms,
and scale AI models behind the firewall.
General :100: Algorithm for developers
Category : Clowd computing,
Capital : $12.9M
Seed : $2.4M
SeriesA: $10.5M
SeriesB:
Rounds: 2 rounds from 10 Investors
Monetize : Providing developer’s tools
Founder: Kenny Daniel
Name : Algorithmia 2013〜
HQ: Seattle
Employee:11-50
Source : https://algorithmia.com/algorithms
Features :
• Algorithmia gives developers the ability to turn algorithms into scalable
web services with a single click.
• Provides two major products: Algorithmia.com, a marketplace for
microservices, and CODEX, a platform for functions and AI models.
Market : Developers

127
Where are AI 100 companies ?
California : 47
Barkley : 2
San Francisco: 23
RedWood City:3
Palo Alto: 5
Mountain View: 5
Menlo Park: 2
Others : 7
New York : 9
Seattle: 4
UK: 6
Israel : 5

Artificial Intelligence (AI) 100 Startups 2017

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