The pharma founder who needed investors to believe the science
Predicting drug bioequivalence from messy clinical PDFs, starting from a HIPAA foundation.
Read the full case study →GenRx had a bold idea: predict drug bioequivalence from messy clinical PDFs. But an idea isn't an architecture, and investors fund what they can see.
They needed to walk into a funding round with a secure, working AI architecture, not a slide.
We started with the foundation, a HIPAA-aligned environment on AWS, before a single prediction ran.
An engine that reads unstructured clinical PDFs (NLP), predicts the key pharmacokinetic metrics (PyTorch), investor-ready.
5.0 / 5.0 on Clutch, quality, schedule, cost.
In regulated domains, the model is the easy part. The architecture that makes it safe and credible is the product.
The car factory still picking parts on paper
A high-volume assembly line that still picked parts by hand off paper lists.
Read the full case study →The security agent that worked in the demo, and broke in the real world
A macOS compliance agent that ran fine interactively, but wasn't something they could ship.
Read the full case study →One API over many gateways, without pulling the whole app into PCI scope
A US gateway provider drowning in bespoke processor integrations.
Read the full case study →From reactive to predictive, on systems actually live in production
A US B2B services operation running on disconnected systems with no single source of truth.
Read the full case study →When matchmaking lived in a few people's heads
A Singapore innovation ecosystem matched startups to investors by hand.
Read the full case study →Scaling remote care without scaling the overhead
TELEMED2U needed to scale remote care, but consultations were inefficient and costs were climbing.
Read the full case study →One records platform across a growing clinic network
A clinic network running on siloed records that couldn't keep up as it grew.
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