We started in the part of AI with the least tolerance for error — healthcare — and built our governance discipline there before offering it to anyone else.
Help enterprises turn AI from a demo into a dependable system — one that's built well, deployed properly, and governed so it can be trusted with real decisions.
A world where "we built an AI system" and "we can prove it behaves correctly" are the same sentence, not two separate projects on two separate timelines.
CollAIborate's platform work began with hands-on clinical AI: IOS dental scan analysis using multi-view CNN classification, and the Agasthya AI clinical chat frontend. That early work taught us something a generic AI vendor rarely learns first-hand — in healthcare, a confident wrong answer is worse than no answer at all.
That lesson became the founding premise of what we build today: CDAI (Contact Doctor AI), our clinical AI orchestration platform with a governance layer built directly into it — not bolted on after. We built the DAG-based workflow engine, the retrieval pipeline, the connector framework, the scheduler and the governance rule engine first for ourselves — then hardened them into a platform others could run.
The Contact Doctor BioMedical LLM family grew out of the same need: a clinical model we could trust enough to put behind our own governance layer, served through a dedicated inference backend rather than called directly from the browser.
From there, the same architecture — orchestration, governance, human-in-the-loop review, audit trails — generalised naturally into enterprise AI applications, machine learning and consulting work outside healthcare. The rigor didn't change; the domain did.
We run CDAI and the Biomedical LLM in production ourselves. We feel outages and edge cases before clients do.
Policy, audit and human review are designed alongside the system, not added after a client asks.
In our own codebase and our clients', we favour additive, validated changes over risky rewrites.
If AI isn't the right tool for a problem, we'll say so before we say yes to the project.
CollAIborate is built and operated by the same engineers who designed CDAI and the Biomedical LLM inference backend — full-stack, from database migrations to model orchestration to the interface a clinician actually sees.
