Healthtech & Wellness

AI features for products where users' wellbeing is on the line and answers must be grounded, auditable and conservative.

Reality check

What usually hurts here.

01Content answers must stay inside clinical-safety boundaries without constant manual review.
02Document intelligence over plans, notes and guidelines fails on real-world formats.
03Engagement features (coaching, check-ins) need memory that behaves correctly over months.
04Costs scale with patient-facing traffic that has sharp daily peaks.
Use cases

Where AI earns its place.

Retrieval-grounded content and education assistants with citations.

Document intelligence over member communications and plan documents.

Medical-image and wellness-signal pipelines with human review.

Longitudinal engagement assistants with carefully scoped memory.

Internal tooling that drafts, classifies and routes with human review.

Technical considerations
01

Design around what the engineering system guarantees (grounding, review loops, auditability); we do not claim certifications we do not hold.

02

Safety behavior is a measurable property: refusal cases and boundary tests belong in evaluation.

03

Data flows are designed around minimum necessary retention from day one.