AI that survives a validated system.

In life sciences, the constraint on AI is not model quality - it is the cost of change in a validated environment. Anything touching GxP has to defend every change to a regulator, now under new AI-specific rules (the EU AI Act, GMP Annex 22) on top of Part 11 and CSV. That is why sandbox demos stall the moment they meet a validated system. We design for that constraint first.

So the highest-leverage early work sits upstream of validated systems - literature review, safety signal detection, submission drafting, manufacturing root-cause analysis. Document-heavy, judgment-heavy, and outside the validation boundary, so we deliver real value without triggering a six-month revalidation cycle - and build the evidence to go deeper later.

We build toward a life sciences platform the honest way: composing working prototypes into a portfolio, not selling one that does not exist yet. Every engagement is a real solution for one client and a reusable piece of the portfolio. The durable value compounds in the data pipelines, encoded workflows, and evaluation harness - not a fine-tuned model.

Readiness → Build → Operate, adapted to how life sciences buys. Expect a committee-driven path: the functional sponsor in Regulatory, Commercial Ops, or Manufacturing sets the priority, but QA, IT security, and validation hold the gates. We plan for those gates from day one, not month three.

Readiness is a structured diagnostic, not a gut check. We score you across eight capability areas that gate agentic work - data, agent architecture, governance, evaluation, human-in-the-lead oversight - on a weakest-link basis, adapted from the CMU SEI and Accenture maturity model. Your ceiling is your weakest area, so the audit ends with the two moves that raise it fastest.

Regulatory scope drives the design. In Readiness we classify the use case: does it touch a GxP-validated system, or sit upstream of one? That sets everything downstream - data integrity, human-in-the-lead review, Part 11 and the newer AI rules, and whether it needs a validation package at all. We keep the first build upstream and low-risk on purpose, and document it to withstand later scrutiny.

A typical first engagement is a 4-6 week paid Readiness audit, then an 8-14 week Build on one upstream workflow with a defined outcome metric - human-in-the-lead, integrated with existing systems, and structured so moving into validated territory stays a deliberate decision.