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Presentation to ABS Alumni
Amsterdam, 13 June 2024
1
CONFIDENTIAL - © 2024 Curiosity Venture Capital B.V.
Investing in AI
2
Introduction
The (Gen)AI revolution
The VC investment landscape
Our investment approach & portfolio
Q&A
Agenda
Introduction
3
4
Introduction:
Herman Kienhuis
Chemical Engineering
McKinsey & Company
INSEAD MBA
ilse media / SanomaDigital (10+ ventures)
SanomaVentures (23 investments)
KPN Ventures (18 investments)
River Venture Partners (20 investments)
Curiosity VC (13 investments)
equality - education - sustainability
5
Introduction:
Curiosity VC
✧ €32 mln early stage venture capital fund
✧ Backed by 95 private investors and the Dutch
government (RVO)
✧ Investing in emerging B2B software companies
(in Benelux, Nordics & Baltics), applying
data/ML/AI technologies to create value for
businesses and society
✧ Team of 7, HQ in Amsterdam, supported by a
co-owners community of advisors and founders
✧ Current portfolio 13 companies, including a.o.:
Strise 󰐘, Dreamdata, BeCause 󰎴, Freesi 󰎿,
QA.tech 󰐴, Altura, Deeploy, Neople 󰐗
From AI evolution
to GenAI revolution
6
7
We’ve entered the decade of ‘intelligent computing’
2020’s
mainframe
computers
1970’s
desktop PC’s
1980’s
portable
computers
1990’s
internet
2000’s
mobile &
cloud
computing
2010’s
intelligent
computing
time
ubiquity
and
value
of
computing
● Big Data
○ 5G/IOT
○ Database
technology
● Processing power
○ GPU’s
○ HPC clusters
● Artificial intelligence
○ Computer vision
○ Natural language
processing
○ Machine learning
○ Neural networks
○ Generative AI 🚀
8
AI technologies have been in development for
decades, but has now entered mainstream
1950: Turing test
1956: Term AI was coined
1997: IBM’s Deep Blue defeats
Gary Kasparov
1998: MIT develops an
emotionally intelligent robot
Kismet
1999: Sony launched pet
robot dog AIBO
1970-1990:
AI winter
1961: First industrial robot
replaced humans at assembly
line
1964: MIT develops pioneering
chatbot ELIZA
1966: A general purpose mobile
robot developed at Stanford
2002: iRobot launched
autonomous vacuum
cleaner robot
2009: Google built first self
driving car
2011: IBM Watson wins Jeopardy!; Apple
launches Siri
2014: chatbot EUGENE passes Turing test;
Amazon launches Alexa
2017: Google introduces transformer model
BERT
2018: OpenAI introduces transformer model
GPT
2020: OpenAI launches GPT-3
2021: Google (Deepmind) launches
AlphaFold
2022: OpenAI launches ChatGPT;
Midjourney launched
2023: Google launches Bard, Anthropic
launches Claude, Mistral launches 7B
50s 60s 90s 00s 10s 20s
9
Advances in computing power have allowed for training
large language models (LLMs) on all www data
Source: Stanford AI Index Report 2024
10
These LLM models caused a breakthrough in
language understanding and performance
Source: Stanford AI Index Report 2024
Image classification (ImageNet Top-5)
Visual commonsense reasoning (VCR)
Natural language inference (aNLI)
Medium-level reading comprehension (SQuAD 2.0)
Multitask language understanding (MMLU)
Visual reasoning (VQA)
English language understanding (SuperGLUE)
Basic-level reading comprehension (SQuAD 1.1)
Competition-level mathematics (MATH)
11
And OpenAI was the first to bring this technology to
the public via ChatGPT…
Source: Demand Newsletter
12
…with Big Tech and other challengers following
● Launched Bard in 2022, Gemini in 2023
● Started integration with Google
products in 2024
● Invested $2B in Anthropic
● Launched Apple Intelligence in 2024,
based on integration of OpenAI models
● Launched first model (Llama, open
weights) in 2023
● Launched Llama 3 in 2024
● Launched 1st model (Claude) in 2023
and Claude 3 in 2024, outperforming
GPT3.5
● Raised $7.6B
● Launched first model (Mistral7B, open
weights) in 2023
● Raised $1.1B
● Invested $13B in OpenAI (since 2019)
● Integrating LLMs in all MS products
● Launched Co-pilot in 2023
● Launched 1st model in 2022 in 100
languages and focused on enterprises
● Raised $885m
● Started by Elon Musk
● Launched first model (Grok) in 2023
● Raised $6B
● Invested $4B in Anthropic
● AWS launched Bedrock AI offering with
multiple hosted models & tools
● Launched ist model (Pi) in 2023
● Team got acquired by Microsoft
● Raised $1.5B
Mistral 󰏃
Cohere 󰎟
Anthropic
X.ai
Inflection
13
GenAI-driven automation is expected to create massive
productivity increases and trillions in economic value
“AI could increase corporate profits by $4.4 trillion per
year” (The economic potential of Generative AI: The
next productivity frontier, June 2023)
“Generative AI could raise global GDP by 7%” (April
2023)
“Generative AI to Become a $1.3 Trillion Market by
2032; GenAI to add about $280 billion of new software
revenue” (June 2023)
“Generative AI has the potential to raise Dutch GDP
with 9%, e.g. €80-85B in 10 years” (March 2024)
14
And companies are already seeing substantial impact
GitHub Copilot helps
developers code up to 55% faster
15
With many jobs exposed to genAI automation, but only a
small fraction at risk of displacement
Source: Implement Consulting research (Mar 2024)
16
This has created a boom in startups and investments,
building on top of this new GenAI infrastructure
Investments ($B)
Source: Dealroom.co State of AI Investing (May 2024)
17
New applications are emerging, aiming to disrupt
existing services markets
Description: Disrupting:
Launched autonomous software developer Devin;
raised $196m
Commercial copywriting assistant; raised $131m
Legal research and writing assistant; raised $106m
Text-to-speech voice generation services; raised $101m
AI-powered photo creation and editing app;
150m downloads, raised $62m
Video translation/localization app; 2m users
OpenAI powered video creation app
Software
development
Marketing services
Legal services
Voice acting
Commercial
photography
Translation services
Film production
Example
18
Potentially creating inflated expectations for the
short term
Source: Gartner hype cycle for AI (Jul 2023)
19
Also there are clear worries about the risks and
potential negative impact on society
Source: McKinsey State of AI in early 2024
20
And it's apparent that AI technology requires guardrails
and regulations to mitigate key risks
Key risks of Generative AI
1. Hallucinations: GenAI systems can generate incorrect
information
2. Harmful Content: GenAI systems can be used to create
harmful content, e.g. porn deep fakes
3. Algorithmic Bias: GenAI systems can generate biased
information based on its unrepresentative training set
4. Mis-information: GenAI systems can be used to create
fake information at scale for the purpose of
misinformation and influencing opinion
5. Intellectual Property: GenAI systems might breach
copyrighted material used in its training set
6. Privacy: GenAI systems might leak personal identifiable
information provided in prompts or training data
7. Cybersecurity: GenAI systems might be vulnerable to
hacks and can be used to create malware & phishing
content at scale
Model fine-tuning, retrieval augmented
generation (RAG) and education
Filters, fingerprinting and legislation
Improve training data and
bias/representation compensation (e.g.
Google Gemini overdid this)
Filters, fingerprinting, and legislation
Licensing, opt-out system and legislation
Anonymized or synthetic training data; PI
filters for prompts, legislation
Update security scans, education, legislation
Mitigation measures
21
The EU is taking the lead in AI regulation, and recently
approved the EU AI Act
Unacceptable
risk
High risk
Limited risk
Minimal risk
Against EU values, infringing fundamental rights
● Cognitive behavioural manipulation of people
● Social scoring; classifying people
● Biometric identification and categorization
● Remote ‘real-time’ biometric identification
● Products falling under other safety rules
● Critical infrastructure
● Education and employment
● Access to essential public and private services (e.g.
healthcare, financial services)
● Law enforcement, immigration, democratic processes
● Chatbots
● Emotion recognition systems
● Generating or manipulating content
All other AI systems
Prohibited
Requirements and controls throughout life cycle
● Implementation of risk management system
● Technical documentation is formalized and kept up
to date
● AIS compliance and declaration to the authority
Minimum transparency requirements
● inform people that they are interacting with an AI
● When relevant, specificies that content has been
artificially generated or manipulated
● Informs users of its general operation
No obligation towards the AI Act
The Venture Capital investment landscape
22
23
What is Venture Capital?
● Young, innovative,
small companies
● Capital to finance
growth &
development
● Investing in equity,
minority
shareholdings
● Long-term horizon
● Backed by private
investors, family
offices, institutional
investors,
corporates and
public funds
KSF’s for Venture Capital Firms
1. Raise funding
● Track record
● LP network
● Differentiating strategy
2. Source deals
● Proprietary data/network
● Data-driven analysis
(outbound)
● Brand presence (inbound)
4. Win deals
● Reputation & personality
● Speed of decision making
● Terms (founder friendly)
5. Support portfolio company
growth
● Expertise & coaching
(board, advisor)
● Support platform
● Follow-on funding (network)
6. Distribute returns
● Manage towards timely exits
● Terms (investor friendly)
● Manage portfolio risk
3. Assess deals
● Assessment processes
● Expert network
● Quality of decision making
Raise
funding
Source
deals
Assess
deals
Win deals
Support
portco
growth
Distribute
returns
8-10 year
fund cycle
24
Venture Capital investments globally are up again
25
Source: CBInsights - State of Venture (Q1 2024)
26
With AI being one of the leading segments
Source: Dealroom.co State of AI Investing (May 2024)
27
Distribution of VC investments per region
Source: CBInsights - State of Venture (Q1 2024)
Venture Capital investments in The Netherlands
28
Source: CBInsights - State of Venture (Q1 2024)
29
In Q1 2024, The Netherlands grew to the #4
spot as VC & startup ecosystem in Europe
Source: Dealroom.co Netherlands Tech Update (Apr 2024)
Our investment approach & portfolio
30
Our Investment Process
Deal sourcing Deal
screening
Deal
Assessment
Term sheet
negotiations
Due
Diligence
• Personal
network
• Investor, advisor
& founder
network
• Startup
databases
• Matchmaking
platforms
• Events
• Pitchdeck
• Product demo
• Key Metrics
• Financials &
forecast
• Captable
• NDA
• Team assessment
• Market &
competition
analysis
• Product USPs &
roadmap
• Customer & sales
pipeline data
• Customer
references
• Unit economics
• Go-to-market
• Hiring plan
• Financial model
• Valuation analysis
• Term sheet • Legal DD
• Commercial DD
• Financial DD
• Tech DD
• Team DD
Transaction
documentation
• Investment
agreement /
share purchase
agreement
• Shareholder
agreement
• Articles of
Association
��
31
500 250 50 10 6 5
32
Criteria for assessment of AI startups
Regular
● Complementary, experienced
team
● Unique solution to a valuable
problem
● Traction with happy customers
● Large, internationally scalable
potential
● Realistic, consistent growth plan
● Fair terms
AI-specific
● Data science & AI knowledge in team
● Access to proprietary training data or
algorithms
● Reinforcing data feedback loop
● Vertical workflow & system integrations
● Customer maturity wrt data/AI
● Compliance with upcoming AI regulation
● AI ethics policy
● Future-proof vs expansion of generic AI
from BigTech
33
How we support portfolio companies
Strategic and financial management
● Help set a clear strategic focus and objectives
● Strengthen financial planning and KPI/metrics management
Commercial development
● Provide customer-centric perspective on proposition and roadmap
● Strengthen data-driven marketing & sales processes
● Introduce to prospects and partners
Organizational & leadership development
● Assist with recruiting of (leadership) talent, introduce to candidates
● Coach founders on personal development and team dynamics/issues
Follow-on fundraising
● Help create fundraising strategy and documentation
● Introduce to investors and support negotiations
General support
● Provide access to experts, best-practices (resources) and p2p and advisor network
● Provide premium access to startup support service providers
pre-seed seed venture growth later-stage
🛠
🎯
󰠼
🛒
💰
Co-owners:
2 General Partners
4 Investment team
16 Expert Advisors
30 Portfolio Founders
34
Neople: virtual co-workers
35
Strise: KYC/KYB automation for banks
36
Because: Sustainability data platform for hotels
37
Altura: AI bid writing for public tenders & RFPs
38
Orq.ai: LLM model orchestration and prompt
management platform
39
Deeploy: Explainable AI deployment software
40
QA.tech: Fully automated software testing
Q&A
41
42
Contact
Amsterdam office:
TNW West
Kon. Wilhelminaplein 1
1062 HG Amsterdam
Herman Kienhuis
herman@curiosityvc.com
Thank you
43

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Presentation by Herman Kienhuis (Curiosity VC) on Investing in AI for ABS Alumni.pdf

  • 1. Presentation to ABS Alumni Amsterdam, 13 June 2024 1 CONFIDENTIAL - © 2024 Curiosity Venture Capital B.V. Investing in AI
  • 2. 2 Introduction The (Gen)AI revolution The VC investment landscape Our investment approach & portfolio Q&A Agenda
  • 4. 4 Introduction: Herman Kienhuis Chemical Engineering McKinsey & Company INSEAD MBA ilse media / SanomaDigital (10+ ventures) SanomaVentures (23 investments) KPN Ventures (18 investments) River Venture Partners (20 investments) Curiosity VC (13 investments) equality - education - sustainability
  • 5. 5 Introduction: Curiosity VC ✧ €32 mln early stage venture capital fund ✧ Backed by 95 private investors and the Dutch government (RVO) ✧ Investing in emerging B2B software companies (in Benelux, Nordics & Baltics), applying data/ML/AI technologies to create value for businesses and society ✧ Team of 7, HQ in Amsterdam, supported by a co-owners community of advisors and founders ✧ Current portfolio 13 companies, including a.o.: Strise 󰐘, Dreamdata, BeCause 󰎴, Freesi 󰎿, QA.tech 󰐴, Altura, Deeploy, Neople 󰐗
  • 6. From AI evolution to GenAI revolution 6
  • 7. 7 We’ve entered the decade of ‘intelligent computing’ 2020’s mainframe computers 1970’s desktop PC’s 1980’s portable computers 1990’s internet 2000’s mobile & cloud computing 2010’s intelligent computing time ubiquity and value of computing ● Big Data ○ 5G/IOT ○ Database technology ● Processing power ○ GPU’s ○ HPC clusters ● Artificial intelligence ○ Computer vision ○ Natural language processing ○ Machine learning ○ Neural networks ○ Generative AI 🚀
  • 8. 8 AI technologies have been in development for decades, but has now entered mainstream 1950: Turing test 1956: Term AI was coined 1997: IBM’s Deep Blue defeats Gary Kasparov 1998: MIT develops an emotionally intelligent robot Kismet 1999: Sony launched pet robot dog AIBO 1970-1990: AI winter 1961: First industrial robot replaced humans at assembly line 1964: MIT develops pioneering chatbot ELIZA 1966: A general purpose mobile robot developed at Stanford 2002: iRobot launched autonomous vacuum cleaner robot 2009: Google built first self driving car 2011: IBM Watson wins Jeopardy!; Apple launches Siri 2014: chatbot EUGENE passes Turing test; Amazon launches Alexa 2017: Google introduces transformer model BERT 2018: OpenAI introduces transformer model GPT 2020: OpenAI launches GPT-3 2021: Google (Deepmind) launches AlphaFold 2022: OpenAI launches ChatGPT; Midjourney launched 2023: Google launches Bard, Anthropic launches Claude, Mistral launches 7B 50s 60s 90s 00s 10s 20s
  • 9. 9 Advances in computing power have allowed for training large language models (LLMs) on all www data Source: Stanford AI Index Report 2024
  • 10. 10 These LLM models caused a breakthrough in language understanding and performance Source: Stanford AI Index Report 2024 Image classification (ImageNet Top-5) Visual commonsense reasoning (VCR) Natural language inference (aNLI) Medium-level reading comprehension (SQuAD 2.0) Multitask language understanding (MMLU) Visual reasoning (VQA) English language understanding (SuperGLUE) Basic-level reading comprehension (SQuAD 1.1) Competition-level mathematics (MATH)
  • 11. 11 And OpenAI was the first to bring this technology to the public via ChatGPT… Source: Demand Newsletter
  • 12. 12 …with Big Tech and other challengers following ● Launched Bard in 2022, Gemini in 2023 ● Started integration with Google products in 2024 ● Invested $2B in Anthropic ● Launched Apple Intelligence in 2024, based on integration of OpenAI models ● Launched first model (Llama, open weights) in 2023 ● Launched Llama 3 in 2024 ● Launched 1st model (Claude) in 2023 and Claude 3 in 2024, outperforming GPT3.5 ● Raised $7.6B ● Launched first model (Mistral7B, open weights) in 2023 ● Raised $1.1B ● Invested $13B in OpenAI (since 2019) ● Integrating LLMs in all MS products ● Launched Co-pilot in 2023 ● Launched 1st model in 2022 in 100 languages and focused on enterprises ● Raised $885m ● Started by Elon Musk ● Launched first model (Grok) in 2023 ● Raised $6B ● Invested $4B in Anthropic ● AWS launched Bedrock AI offering with multiple hosted models & tools ● Launched ist model (Pi) in 2023 ● Team got acquired by Microsoft ● Raised $1.5B Mistral 󰏃 Cohere 󰎟 Anthropic X.ai Inflection
  • 13. 13 GenAI-driven automation is expected to create massive productivity increases and trillions in economic value “AI could increase corporate profits by $4.4 trillion per year” (The economic potential of Generative AI: The next productivity frontier, June 2023) “Generative AI could raise global GDP by 7%” (April 2023) “Generative AI to Become a $1.3 Trillion Market by 2032; GenAI to add about $280 billion of new software revenue” (June 2023) “Generative AI has the potential to raise Dutch GDP with 9%, e.g. €80-85B in 10 years” (March 2024)
  • 14. 14 And companies are already seeing substantial impact GitHub Copilot helps developers code up to 55% faster
  • 15. 15 With many jobs exposed to genAI automation, but only a small fraction at risk of displacement Source: Implement Consulting research (Mar 2024)
  • 16. 16 This has created a boom in startups and investments, building on top of this new GenAI infrastructure Investments ($B) Source: Dealroom.co State of AI Investing (May 2024)
  • 17. 17 New applications are emerging, aiming to disrupt existing services markets Description: Disrupting: Launched autonomous software developer Devin; raised $196m Commercial copywriting assistant; raised $131m Legal research and writing assistant; raised $106m Text-to-speech voice generation services; raised $101m AI-powered photo creation and editing app; 150m downloads, raised $62m Video translation/localization app; 2m users OpenAI powered video creation app Software development Marketing services Legal services Voice acting Commercial photography Translation services Film production Example
  • 18. 18 Potentially creating inflated expectations for the short term Source: Gartner hype cycle for AI (Jul 2023)
  • 19. 19 Also there are clear worries about the risks and potential negative impact on society Source: McKinsey State of AI in early 2024
  • 20. 20 And it's apparent that AI technology requires guardrails and regulations to mitigate key risks Key risks of Generative AI 1. Hallucinations: GenAI systems can generate incorrect information 2. Harmful Content: GenAI systems can be used to create harmful content, e.g. porn deep fakes 3. Algorithmic Bias: GenAI systems can generate biased information based on its unrepresentative training set 4. Mis-information: GenAI systems can be used to create fake information at scale for the purpose of misinformation and influencing opinion 5. Intellectual Property: GenAI systems might breach copyrighted material used in its training set 6. Privacy: GenAI systems might leak personal identifiable information provided in prompts or training data 7. Cybersecurity: GenAI systems might be vulnerable to hacks and can be used to create malware & phishing content at scale Model fine-tuning, retrieval augmented generation (RAG) and education Filters, fingerprinting and legislation Improve training data and bias/representation compensation (e.g. Google Gemini overdid this) Filters, fingerprinting, and legislation Licensing, opt-out system and legislation Anonymized or synthetic training data; PI filters for prompts, legislation Update security scans, education, legislation Mitigation measures
  • 21. 21 The EU is taking the lead in AI regulation, and recently approved the EU AI Act Unacceptable risk High risk Limited risk Minimal risk Against EU values, infringing fundamental rights ● Cognitive behavioural manipulation of people ● Social scoring; classifying people ● Biometric identification and categorization ● Remote ‘real-time’ biometric identification ● Products falling under other safety rules ● Critical infrastructure ● Education and employment ● Access to essential public and private services (e.g. healthcare, financial services) ● Law enforcement, immigration, democratic processes ● Chatbots ● Emotion recognition systems ● Generating or manipulating content All other AI systems Prohibited Requirements and controls throughout life cycle ● Implementation of risk management system ● Technical documentation is formalized and kept up to date ● AIS compliance and declaration to the authority Minimum transparency requirements ● inform people that they are interacting with an AI ● When relevant, specificies that content has been artificially generated or manipulated ● Informs users of its general operation No obligation towards the AI Act
  • 22. The Venture Capital investment landscape 22
  • 23. 23 What is Venture Capital? ● Young, innovative, small companies ● Capital to finance growth & development ● Investing in equity, minority shareholdings ● Long-term horizon ● Backed by private investors, family offices, institutional investors, corporates and public funds
  • 24. KSF’s for Venture Capital Firms 1. Raise funding ● Track record ● LP network ● Differentiating strategy 2. Source deals ● Proprietary data/network ● Data-driven analysis (outbound) ● Brand presence (inbound) 4. Win deals ● Reputation & personality ● Speed of decision making ● Terms (founder friendly) 5. Support portfolio company growth ● Expertise & coaching (board, advisor) ● Support platform ● Follow-on funding (network) 6. Distribute returns ● Manage towards timely exits ● Terms (investor friendly) ● Manage portfolio risk 3. Assess deals ● Assessment processes ● Expert network ● Quality of decision making Raise funding Source deals Assess deals Win deals Support portco growth Distribute returns 8-10 year fund cycle 24
  • 25. Venture Capital investments globally are up again 25 Source: CBInsights - State of Venture (Q1 2024)
  • 26. 26 With AI being one of the leading segments Source: Dealroom.co State of AI Investing (May 2024)
  • 27. 27 Distribution of VC investments per region Source: CBInsights - State of Venture (Q1 2024)
  • 28. Venture Capital investments in The Netherlands 28 Source: CBInsights - State of Venture (Q1 2024)
  • 29. 29 In Q1 2024, The Netherlands grew to the #4 spot as VC & startup ecosystem in Europe Source: Dealroom.co Netherlands Tech Update (Apr 2024)
  • 30. Our investment approach & portfolio 30
  • 31. Our Investment Process Deal sourcing Deal screening Deal Assessment Term sheet negotiations Due Diligence • Personal network • Investor, advisor & founder network • Startup databases • Matchmaking platforms • Events • Pitchdeck • Product demo • Key Metrics • Financials & forecast • Captable • NDA • Team assessment • Market & competition analysis • Product USPs & roadmap • Customer & sales pipeline data • Customer references • Unit economics • Go-to-market • Hiring plan • Financial model • Valuation analysis • Term sheet • Legal DD • Commercial DD • Financial DD • Tech DD • Team DD Transaction documentation • Investment agreement / share purchase agreement • Shareholder agreement • Articles of Association �� 31 500 250 50 10 6 5
  • 32. 32 Criteria for assessment of AI startups Regular ● Complementary, experienced team ● Unique solution to a valuable problem ● Traction with happy customers ● Large, internationally scalable potential ● Realistic, consistent growth plan ● Fair terms AI-specific ● Data science & AI knowledge in team ● Access to proprietary training data or algorithms ● Reinforcing data feedback loop ● Vertical workflow & system integrations ● Customer maturity wrt data/AI ● Compliance with upcoming AI regulation ● AI ethics policy ● Future-proof vs expansion of generic AI from BigTech
  • 33. 33 How we support portfolio companies Strategic and financial management ● Help set a clear strategic focus and objectives ● Strengthen financial planning and KPI/metrics management Commercial development ● Provide customer-centric perspective on proposition and roadmap ● Strengthen data-driven marketing & sales processes ● Introduce to prospects and partners Organizational & leadership development ● Assist with recruiting of (leadership) talent, introduce to candidates ● Coach founders on personal development and team dynamics/issues Follow-on fundraising ● Help create fundraising strategy and documentation ● Introduce to investors and support negotiations General support ● Provide access to experts, best-practices (resources) and p2p and advisor network ● Provide premium access to startup support service providers pre-seed seed venture growth later-stage 🛠 🎯 󰠼 🛒 💰 Co-owners: 2 General Partners 4 Investment team 16 Expert Advisors 30 Portfolio Founders
  • 36. 36 Because: Sustainability data platform for hotels
  • 37. 37 Altura: AI bid writing for public tenders & RFPs
  • 38. 38 Orq.ai: LLM model orchestration and prompt management platform
  • 39. 39 Deeploy: Explainable AI deployment software
  • 40. 40 QA.tech: Fully automated software testing
  • 42. 42 Contact Amsterdam office: TNW West Kon. Wilhelminaplein 1 1062 HG Amsterdam Herman Kienhuis herman@curiosityvc.com