Industry
AI systems for healthcare and life sciences
Careful, evaluation-first AI systems for knowledge, operations, and research support — designed around privacy, quality, and human oversight.
Common problems
- Sensitive data and clinical/process risk demand strong controls.
- Generic assistants invent answers where evidence must be grounded.
- Teams need measurement before any broad deployment.
Systems we engineer
- Grounded retrieval with strict access and citation patterns
- Human-reviewed workflows for high-impact outputs
- Evaluation suites for quality and safety regressions
- Governance artifacts for internal review boards
Outcomes
- Higher trust in AI-assisted knowledge work
- Explicit human control on sensitive steps
- Release discipline for model and prompt changes
- Internal ownership after delivery
Start with production readiness
We map your constraints, risk, and architecture options before scale — then deliver systems your organization can operate.