70% of AI leaders cannot explain how specific AI model decisions or predictions are made, and only 35% said their organization made an effort to use AI in a way that was transparent and accountable. Ethics and AI have become a central conversation in the tech industry, driven by the lack of understanding of data models, what information they are trained on, and the risk of bias. This is especially critical in sectors like healthcare, where algorithmic bias can leave out significant portions of a population and lead to devastating results. Attendees of this session will: - Understand the inherent challenges in utilizing artificial intelligence in a way that is transparent and accountable. - Why you need to pay more attention to your data models and how you are are using & training AI and deep learning. - How to develop a framework for identifying and overcoming inherent biases in data sets to ensure that your AI is driving more equitable products.

1. Building a Vertical
SaaS company in a
Horizontal SaaS world
Dipanwita Das, CEO, Sorcero
August 2022
1

2. Agenda
1
2
3
4
5
6
2
Introductions
The Vision for Vertical SaaS
Sorcero’s Journey
Pros & Cons of Vertical SaaS
Vertical SaaS & AI: A Perfect Match for the
Enterprise
Surprises and Learnings

3. Introducing Sorcero and my journey
3
Challenge of Disseminating Complex Public
Health Data in 20 countries to stakeholders
+
World’s medical knowledge in hardest data
format: unstructured technical language
=
Our mission: to improve patient outcomes
through effective use of the world’s knowledge.

4. The Evolution of SaaS
4
Vertical SaaS
companies sell comprehensive,
cross-functional mission-critical
technology to one industry.
Horizontal SaaS
companies do a few things many
organizations need and are valued based
on a massive, total addressable market.

5. Enterprise Horizontal SaaS vs. Cloud Platforms
5
Broadly applicable enterprise software uses cases are continuously built and deployed.
Horizontal SaaS entrants compete with 1,000s of Cloud apps consumable via credits.
AWS
Azure
GCP

6. The Vision of Vertical SaaS
Focus: A software company focussed on owning a
single market with mission-critical products, rather
than small shares across a number of markets.
Win: Only one or two companies can dominate the
vertical market, trading breadth for market share and
depth.
Expand: The best vertical SaaS have a layer cake
approach to product and always have a product suite.
Extend: Vertical SaaS develops their second product
years before the first product slows down.
6
Thanks to Dave Yuan at Tidemark

7. Sorcero: How did we get here?
7
The challenge with growing
unstructured healthcare content
Tested 3 markets
● Life Sciences
● Insurance
● Healthcare
Increasing data regulations and
data needs in Life Sciences
Breakthroughs in
large language AI
Discovery: Medical Affairs in Life
Sciences owns Scientific & Clinical
Data delivery to Healthcare &
Insurance in a $11 trillion market

8. Enterprise health data is vast and messy, perfect for
domain-specific AI learning unstructured data types
8
DATA PREVALENCE

9. 9
Sorcero focused on eliminates manual reporting, bringing to bear
powerful analytical tools via Clarity platform workflows and AI Analytics
Clinical Trials
Congresses
Social Media
Clinical Data
Medical Guidelines
Publications
EXTERNAL MEDICAL CONTENT
CRM Data
Advisory Boards
Medical Inquiries & Responses
Medical Education Materials
KOL / HCP Profiles
ENTERPRISE MEDICAL CONTENT
Field Medical
Publications Teams
Medical Information
Health Economics (HEOR)
Medical Analytics
Senior Leadership
MEDICAL FUNCTIONS
Medical Education
Non-Registrational Clinical
Trials (nRE)

10. Vertical SaaS companies deliver value to their
market by serving mission-critical industry specific
workflows.
Domain-specific AI focuses on delivering precision
processing of industry-specific data, learning
specific workflows for insights.
Enterprise AI and Vertical SaaS becomes an
inextricable part of their customer’s value chain,
with domain-specific workflows and data
processing that unlocks messy enterprise data to
augment mission-critical decisions.
10
Vertical SaaS & AI: A Perfect Match for the Enterprise

11. Deploy AI alongside Expert Workflows to get Enterprise Adoption
11
Example - AI in Pharmacovigilance:
Sorcero models achieve very high accuracy, but if
a single new side-effect is missed, it can
significantly impact health outcomes.
At Sorcero, we shifted the focus from scoring to
enhance customer’s workflow to identify the
relevant documents faster and less effort -
reducing human error, not full automation.

12. 12
Surprise and Learnings
Life Sciences is incredibly ahead and behind other industries
in adopting technology. Vast investments in AI drug
discovery, little in efficiency. Lean into “weak” spots.
Domain-specific AI can achieve much higher accuracy that
general-domain AI, due to targeted problem space.
Vertical SaaS is still not understood by many investors that
are still focuses on “unencumbered growth”.
Go Global Fast many verticals have major clusters outside of
the United States hungry for technology and willing to invest.
Pick a Vast Vertical Life Sciences is the highest-margin
business in the world, with $2.4 trillion in revenue.
Healthcare is $11 trillion. Markets are massive in depth.

13. Language Intelligence for
Life Sciences
∵ ∑ (human + AI) > human ⊻ AI
13