Industry
Healthcare — systems first, AI where it's earned
Healthcare data is high-stakes and heavily regulated, and we treat it that way. Our healthcare work leads with systems integration and data engineering — the connective tissue between EHRs, claims, and operational systems — and we bring AI into the picture only in narrow, auditable places where getting it wrong isn't an option.
Where we work in your stack
Three problems we solve for healthcare organizations
EHR & systems integration
Connecting electronic health record systems, billing platforms, and operational tools without disrupting the clinical workflows that depend on them.
Healthcare data engineering
Pipelines and data models built to the compliance and auditability standards healthcare demands — not retrofitted onto a generic data stack.
Conservative AI applications
Administrative automation, documentation support, and retrieval over internal knowledge bases — deployed only where a human stays in the loop and every output is traceable.
A note on how we talk about healthcare AI
We won't claim AI can make clinical decisions, and we're wary of anyone who does. Where we apply AI in healthcare settings, it's scoped to administrative and operational tasks with clear human oversight. We're building out published examples of this work. Ask us for specifics.