Quantum has developed an AI system for natural language interactions that can understand questions, access information, and provide answers. Their semantic-based NLP technology translates natural language into executable machine logic. They have an existing product for sale that large data and software companies are contracting with. Their goal is to build an advanced language interface that can understand concepts at different levels and provide explainable, verifiable answers through dynamic adaptation.

1. The World’s Most Advanced
AI For Human Machine
Language Interface
Solving the last major problem in NLP/NLU

2. Overview
Quantum developed a unique Semantic based NLP technology,
and we are creating composite AI to leverage advantages
from probabilistic and neurosymbolic models on the way to true
human-machine collaboration
While competition that have previously raised investments
are still developing their product, Quantum have a product
in sale right now
The value of the addressable market is in the 10s of billions
if not trillions.
1. OEM for data vendors
2. OEM for SaaS vendors
3. Enterprise information retrieval (direct & system integrators)
2

3. Building Quantum: Visionary Team
He was awarded the United Nations Global
Young Entrepreneur Award at the UN’s 7th
World Summit of Young Entrepreneurs in
recognition of his work. He founded and built
genetics and software companies in Europe
and the US.
He was also the Director of AI at SRI which
produced advanced language systems
like Apple Siri and Viv.
He co-founded the American Association
for Artificial Intelligence and central
player in the AI/NLP world in Silicon Valley. His
PhD is from Stanford University.
He started IBM’s move into AI and built the
underlying technologies. When he left IBM,
he moved over to buy-side of technology
and became the CIO of illustrious companies
such as Silicon Graphics, Synopsys, Altera
and Brocade.
He also created Silicon Valley’s two largest
CIO networking groups and the #1 cyber
security program in California.
3

4. While McKinsey predict that by 2025 seamless
interactions among humans and machines will
likely be a corporate standard,today many
business problems still get solved through
traditional approaches and take months or
years to resolve.
4

5. Problem
Whyisn’tnaturallanguagealreadybeingused?
Accuracy
Canonlygetstatisticalanswer-notaccurate,
i.e.bestguess.Itisnotgoodenoughforourtasks
andcannotunderstandhowanswerwasderived.
What’swrongwithtoday’s
NLP/NLUthatdonotprovidethis?
Today’sNLP/NLU
cannotprovide:
Differentlayersofneuralnet-cannot
understandhowanswerwasderived.
Explainability
Canonlyruntestsuites,notverifyhowan
answerwasprovidedorgetthesameanswer
withcertainty.
Verifiability
Havetore-trainoneachnewdataset.
DynamicAdaptation
Thatleadtolower
speedandqualityof
businessdecisions
intheenterprises.
5

6. Solution
Ask a plain English
question – get an
immediate answer
No need for
technical knowledge
Quantum’s Language-
powered AI platform
enables business users to do
complex information retrieval
and analytics without having
to learn any new skills.
?
6
Quantum can deliver 5-10x ROI
in time gains on information
acquisition

7. Technology
At Quantum, we’ve developed a
unique semantic-based NLP/NLU
technology to provide non-technical
users insights from data.
Quantum’s technology understands concepts,
and auto-translates them into machine logic
and code (actions, sub-routines, queries)
7

8. The core of Quantum’s AI based technology
Neuro-
symbolic
Computation
Neural
Probabilistic
Logic Based
Approaches
Knowledge
Representation
Neural
Networks
Machine
Learning
Deep
Learning
8

9. How it works
1
2
Quantum interprets human language and
translates it into executable machine logic
Ask a
question
Access the
information
Book a LIVE demo
Book a LIVE demo
9

10. Initial traction
Initial sale + paid
POCs with major data
and SaaS vendors in
contracting process
Strong pipeline
of data vendors &
SaaS companies
(especially Financial &
General data)
10
Already executed
POCs on
Salesforce and SAP

11. Market & target markets
Information retrieval
BUSINESS
INFORMATION 3 3
5
2
SELF SERVICE
information
retrieval & analytics
OEMs
$Trillion
Information retrieval +
information input
Advanced Language AI
Step 1 Step 2
Step 3
ENTERPRISE SOFTWARE
LANGUAGE
INTERFACE
IOT
Smart
City
Robotics
Consumer
Inforation
...
Internal
analytics
1 2 by 2026, Allied MArket
Research 2020
3 IDC 2016 4 IDC 2018 5 McKinsey
2016
11

12. The competition & benefit over competition
Raised
Product
Technology
Leadership
ADE AI
since 2021
INF AI
since 2022
QUANTUM
since 2013
Product NOT
in the Market
Product expected
in 5 years
Product in sale
right now!
AI, NLP/NLU
AGI
AI, NLP/NLU
Explainability
Verifiability AGI
AI
AGI
12

13. True Human - Computer Interaction
Purpose Growth process
Each step in the development
and evolution of Quantum’s
tech/products will live by itself
and provide value to customers.
So we continuously:
Reinvest revenues into building
company and technology
Learn from practical users
and different customer types
revalue and uses
Incorporate learnings into
next step of evolution to
enhance value
13
2
1
Release
products
Create
revenue
Reduce business &
technology risk
Reduce external
investment
Ensure success of
company regardless
of achieving
overarching vision

14. Target audience
A game changer for business processes in Enterprizes:
Implement real-time information
driven business processes
Take effective immediate actions
based on relevant information
Access any information simply by
asking the question in normal
business language
Extract value from data investment
and system implementation
Enable self-service information
access to the entire organization
Contentiously extract value from
data after one-time onboarding of
fields and vocabulary
Enhance Availability
of information for
Business users
for
business
teams
for
it
&
Data
teams
Reduce need for support
from (and load on)
IT & Data Teams
14

15. Business model (SaaS)
Go to market
through partners
with economics
suited to them
Non-
recurring
engineering
expenses
15

16. Go-to-Market
OEM for data vendors & SaaS
1
2 3
1
2 3
16

17. Roadmap
Science -level problems
Technology approach
Brittleness
Scalability
Product Dev NLP/NLU
Scalable Platform
- Accuracy
- Explainability
- Verifiability
- Dynamic Adaptation
SIIA
Most innovative
+Overall Winner
1st
Prototype
2nd
Prototype
3rd
Prototype
Initial Customer
Trials
Unreasonable
Fellowship
DEWA Proof
of Concept
Commercialization
- Pipeline
- Team (sales,
marketing, etc)
Fintech Innovation
Lab
2014 2015 2016 2017 2018 2019 2020 2021 2022
17

18. Investment & use of funds
USE OF
FUNDS
Purpose of raise [placeholders, to
be completed with CFO/CRO/CS]:
Total funding
needed
$XXM USD
$XM USD bridge
18

19. Contacts
kgch@quarrio.com

20. Appendix

21. Searching for information costs time & money
searching for
information
Typical employee spends
1.8 hours of each day
that already exists
elsewhere
Data professionals spend 20%
of their time building information
. . .
1.8
hours
/day
20%
of time

22. 6
The examples, Data Problem
We are losing new
sales and customer
opportunities!
I’m so tired of
waiting for IT to
get back to me
The data they
want are in
different systems
and apps
Everyone here
wants a different
way to query the
same data
How do I give
and limit
access?
I know the data
exists, but I don’t
know how to find
what I’m looking for
I need the
information now.
I don’t have the time
to search for it
Company users are frustrated IT departments are
under-staffed and overwhelmed

23. -$17,000
per employee per year is
estimated lost because of lack of
data access when needed