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Health data carries the highest sensitivity classification of almost any sector. Products here need data handling that's defensible under scrutiny, not merely functional in a demo.
Health data sits at the top of almost every sensitivity classification scheme that exists, and a product that treats it like ordinary application data will eventually fail a security review, a client's procurement audit, or both. We classify data sensitivity before any schema decision is made, and design access control and audit logging directly against that classification — not as a generic best-practice layer applied uniformly regardless of what's actually being stored.
Clinical systems integration is its own discipline because the systems on the other end were rarely designed to be integrated with — many predate modern API conventions entirely. We scope integration work around the existing clinical workflow rather than asking clinical staff to adapt to a new one, and where AI features are involved, we scope them specifically as decision support with a human sign-off step preserved, rather than as autonomous clinical decisions.
Relevant capabilities
Sensitivity classification happens before any schema or architecture decision, and access control and audit logging are designed directly against that classification rather than applied as a generic layer afterward.
In most cases, yes, though the integration approach depends heavily on the specific system's age and interface. We scope this explicitly before committing to an approach, because many clinical systems predate modern integration standards.
We scope AI features in this sector as decision support with a human sign-off step preserved, not as autonomous clinical decision-making. That boundary is a deliberate design choice, not a current technical limitation.
Tell us the constraint you're actually up against — regulatory, technical, or both.