Case Study: Basys.ai
Basys.ai is a B2B SaaS platform that supports the clinical decision-making for doctors at hospitals.
Author’s Note: Welcome to the newest version of the Case Studies! This article and following Case Studies are going to be less focused on product-market fit and more of a granular examination of the core parts of a startup. The Case Study is meant to reflect a long-form, qualitative version of a due diligence process for a startup raising funding.
I hope you enjoy!
Introduction:
Jie Sun and Amber Nigam are Harvard alums and have worked for 17 years combined in AI and healthcare. They have previously founded a venture and successfully exited it. They have also been inventors of 3 patents and have authored 5+ research that has been published in top machine learning conferences and journals. The founders instructed data science at MIT before. Besides, they have recently won the prestigious MIT 100K Accelerate Competition and were selected as a semi-finalist for Harvard’s President Innovation Challenge. Both founders were named 40 under 40 by the Boston Congress of Public Health in 2022.
Executive Summary:
Problem: Metabolic health based and chronic diseases are associated with bad patient outcomes and account for the 90% of the total healthcare costs in the US and accounts for almost 20% of GDP. For providers and payors, it is a huge problem as they lose revenue because of the bad outcomes and overbudened system.
Market: There are more than $40B annual market just for diabetes. The market is much larger market for metabolic health.
Solution: We are a B2B SaaS platform that supports the clinical decision-making for doctors at hospitals. We use proprietary AI technology (patent pending) to track, predict, and intervene to improve treatment outcomes for metabolic health.
Team: We have extensive experience in previously founding a company, healthcare, and data science besides being classmates at Harvard.
Hiring: These are the three roles they are hiring for:
Data Scientist
Fullstack developer
Head of Sales
Case Study: Basys.ai
Tell me about the problem the startup solves.
Basys.ai enables providers and hospitals to deliver better care for the metabolic health of patients. Providers are the critical component of the system that most competitors have excluded from their processes. Besides, access to clinically validated data is key to the success of any metabolic health solution.
Chronic conditions and metabolic health-based diseases almost account for 20% of the GDP of the US. To an individual patient, it severely affects the quality of life. Given the trend that people have started adopting healthy habits, there is a light at the end of the tunnel.
My (Amber’s) dad had unmanaged diabetes for 25 years, which was not a great experience for me. I do not want anyone to be scarred by it as I was.
Tell me about the market the startup serves.
We have chosen to go after providers (hospitals) and not directly to the patients because they are a critical component in the process. AI without context is garbage in, garbage out.
We have spoken to more than ten hospitals and 50 doctors before building our solution for them. The three most common pain points captured in our customer research are:
Doctors have limited time.
Hospitals seek ROI.
There is growing awareness about the role of AI in healthcare.
In the future, we hope to learn the following from our customers:
Clinical validation of the product
Identify the metrics of impact and value to the providers and hospitals
Prepare to reach out to payors (insurance companies) and prove their ROI through our product.
Our competitors are:
Other clinical decision support companies
EHR giants like Epic and Cerner
Big tech companies going after the healthcare market.
We plan to increase our total addressable market by reaching out to the payors (they are highly incentivized by our solution and have money).
Tell me about the solution the startup created.
We have built an AI-first B2B SaaS platform for providers to manage the metabolic health of patient. Our solution is differentiated in four key ways:
Access to clinical data from the best and the largest metabolic institute
Proprietary AI tech (patent filed) on the progression of metabolic diseases
Accurate and explainable deep learning solutions for managing diseases
Designed to save time for doctors and increase revenue for the hospitals
Our solution is novel in the following ways:
We help providers optimize their data to generate more revenues, reduce costs, and achieve better patient outcomes.
We use data synthesis to generate large datasets and apply adversarial networks to achieve more predictive power.
Our business model is differentiated in who we focus on. Instead of reaching out to the employers and then employees, we go to the providers and hospitals. This helps us get clinically validated data. For clinical AI, data is the most cog in the wheel. To the best of our knowledge, none of the companies in metabolic health have taken this approach.
Most companies end up selling to the payors (insurance companies), and payors require actuarial models for evaluating their ROI. Actuarial models can only be good if you have good-quality data. Our focus is to target the core of the clinically validated data - providers and hospitals, for making our actuarial models. Last, through this, we would be automating claim resolution, which is a win-win for both providers and payors.
There will be network effects as we scale to the payors because our product has direct economic advantages.
Product-market fit for Basys.ai is adoption by the payors based on the actuarial models through our partnerships with the providers. Our north star metric is annual recurring revenue (ARR). Basys’s beachhead market is providers and hospitals, and the next target are payors.
In fact, we got our first customer in less than 11 months, whereas the typical sales cycle in our domain is typically two years. On the repeatability aspect, our solution results in actual savings and an increase in revenue for hospitals. So, they are incentivized to use our offering.
Tell me about the team behind the startup.
Our vision is to be the market leader in clinical decision support for providers to enable a seamless standard of care. The other plan is to standardize the insurance reimbursement process. The plan is to use data to create a disease progression model to drive better patient outcomes. This will help diagnose diseases faster and take prophylactic measures, thus reducing the cost for the payors.
Each founding team member’s skill set blends unique healthcare and AI skills together. We respect each other and have worked together for many years. We have both worked for almost a decade each and realize that both want to start their own ventures. While one has previous startup experience, the other has significant healthcare experience. Both have a data science background and an MS in Health Data Science from Harvard.
Our management style is collaborative but self-driven. The company’s culture is built around a flat hierarchy and autonomy. Each team member is responsible for their respective P&Ls and has a high sense of ownership and accountability.
Here are the backgrounds of some of our first few hires:
Chief Medical Officer - MD and 20 years of experience as CMO of the largest healthcare organizations;
Data Scientist - 7 years of experience in data science
Software Developer - 5 years of experience in development;
Currently, Basys.ai is gearing up to scale several hospitals, and we need individuals who can help us operate at scale.
Who are you trying to hire, and why?
The top three roles our company needs to fill are:
Data Scientist
Fullstack developer
Head of Sales
Here are the biggest pain points each hire needs to solve:
Has to be able to handle deployment
Should know backend, frontend, and database
Aligned with the vision and ethics of the startup
Here is the career trajectory for each role:
For Role #1, there’s a steep learning curve to become the Chief Scientific Officer in a few years. We want them to lead a team and work closely with the management, product, and sales teams.
Role #2 has a steep learning curve to become the Head of Engineering in a few years. We expect them to lead a team of developers and possibly a technology vertical within the organization.
Role #3 has a steep learning curve to becoming the Chief Sales Officer in a few years. We want them to handle their own PnL.
As founders, we are extremely focused on team members’ growth and career development, which we believe sets us apart from other startups and incumbents in this space.
Three Cool Founders You Should Know About:
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Michal Depa, Founder of StataDX: StataDX is building the world's first point-of-care diagnostics platform for Neurology.
Derek Haas, Founder of Avant-garde Health: Avant-garde Health partners with leading health care providers committed to improving the value of care.
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