Building for investors from day one.
A stealth-mode pharmaceutical AI and intelligence platform needed to move fast—but not recklessly. The founding team had deep domain expertise in pharma consulting, insurance algorithms, and health sector investing. What they needed was someone to ensure their technical decisions would hold up to investor scrutiny.
I came in early to provide advisory on technical stack decisions. The goal wasn't just to build something that worked—it was to build something that demonstrated sound technical judgment to investors and potential acquirers down the road.
The product had its own CTO. My role was to bring a US-centric investor lens to the technical conversation, helping ensure the architecture would tick the boxes that matter when raising capital.
Pharmaceutical intelligence at scale.
An AI-powered platform ingesting and analyzing pharmaceutical data to deliver actionable intelligence for industry decision-makers.
Advisory at the foundation.
Investor Lens
Bringing US-centric investor perspective to technical decisions. Ensuring the stack and architecture would demonstrate sound judgment to VCs and potential acquirers.
Stack Architecture
Guiding technology choices that balanced speed-to-market with long-term scalability. Building a foundation that could grow with the business.
Data Pipeline Design
Supporting the design of data factories pulling CMS Medicare Part D prescription data—millions of records on prescribing patterns across the US.
Entity Formation
Assisted with registering the corporate entity, ensuring the business structure aligned with fundraising and growth objectives.
Speed without shortcuts.
The pressure was to get to market as fast as humanly possible. But cutting corners on technical decisions would come back to haunt them—either in scaling problems or in investor due diligence.
We needed to build quickly while maintaining high quality in UI/UX and making defensible technical choices. This was also pre-ChatGPT—early-stage AI and NLP implementation when the tooling was far less mature than it is today.
The platform launched with a technical foundation built to withstand investor scrutiny. Data pipelines successfully ingested CMS Medicare prescription data, and early NLP capabilities were implemented before the LLM wave made such features commoditized.
Built to evolve.
The platform is still active and currently being repurposed for new opportunities in the pharmaceutical intelligence space. The technical foundation we established continues to support the product's evolution.
Sometimes the most valuable work isn't the most visible. Advisory engagements like this one are about ensuring the decisions made in the early days don't become technical debt that haunts the business later.