Industry
Healthcare Software Engineering
Healthcare software fails when it ignores the clinic: the interruptions, the shared devices, the low tolerance for friction. We build patient-facing and clinical products that fit real workflows, handle sensitive data properly, and interoperate with the systems already in the building.
- HIPAA and GDPR aware
- FHIR and HL7
- Designed for the clinic
120k
Patients on a care companion we built
4.8
Average app store rating on that product
FHIR
The standard we integrate to, not a custom API
Where we help
What we build
Patient-facing apps
Companion apps, care pathways, symptom tracking and messaging that patients keep using past week one.
Clinical and provider tools
Interfaces designed for shared devices, interruptions and speed, so they save clinician time rather than costing it.
Interoperability and integration
FHIR and HL7 integration with EHRs, labs and devices, so your product is part of the record, not a silo.
Data platforms for research
De-identified, governed data pipelines for analytics and life-sciences research.
What is different here
How we handle sensitive data
Privacy by design
Data minimisation, encryption, access logging and retention rules built in from the first architecture diagram.
Safety cases where they matter
For features that influence care, we document the risks and the mitigations, and we test them.
Accessibility as standard
WCAG 2.2 AA, because the people using health software span every ability and every device.
Auditable and explainable
Especially for any AI: what data it used, what it recommended, and who decided.
FAQ
Healthcare & Life Sciences FAQ
Are you HIPAA compliant?
HIPAA compliance is an organisational programme, not a vendor badge. We build to its technical safeguards, sign a BAA where relevant, and support your compliance work with documentation and design that stands up to review.
Can you integrate with our EHR?
Yes. We work with FHIR and HL7 v2, and with the specific APIs of the major EHR vendors. We scope integration carefully because it is usually the part that slips.
Do you build AI features for healthcare?
Yes, with the extra rigour the domain needs: grounded outputs, human decision-making, evaluation on clinical test sets, and clear disclosure. We will tell you when a use case is not ready for AI.
Have a digital health product to build?
Tell us what you're working on. We come back within two business days with a point of view and next steps.