@Human forHealthcare and social care
AI that helps clinicians, with patient data kept where it belongs.
Build referral triage, rostering and patient-facing assistants with special-category data governed from the first line. Clinicians approve every decision, and the data register follows patient data all the way into AI.
- GDPR Article 9 ready
- Clinician sign-off
- Self-hosted
What's slowing AI down in healthcare and social care
The pressure is real, and so are the rules. Here's what teams like yours are up against.
Health data is special-category data
GDPR sets a higher bar for processing health data. You need to know exactly where it goes, including into prompts and AI outputs.
Patient triage AI is high-risk
The EU AI Act lists emergency healthcare patient triage systems as high-risk, with duties for human oversight, logging and risk management.
Good projects stall in review
Data protection officers can't sign off what they can't see. Without a clear data map and approval trail, AI pilots never reach patients.
Enterprise systems you could build with @Human
Beautiful, everyday tools for your teams and the people you serve, each one a governed project from the first line.
Referral Triage
Referrals arrive sorted by urgency, with missing information chased automatically by rule. An assistant suggests a priority, and a clinician confirms it.
Ward Rostering
Shifts, attendance, leave and corrections for every ward, with decisions surfaced to the right manager.
My Clinic
Patients check appointments and ask everyday questions. Anything clinical is flagged straight to the care team.
Example apps with illustrative data, showing what can be built on @Human.
Governance built for health and care
Every @Human app moves through six stages, from setup to compliance evidence. These are the parts that matter most to you.
Special-category data mapped
The register records every place health data lands, including prompts, assistant memory and outputs, with retention and recipients.
Clinician in the loop
Approval gates and role permissions make sure AI suggests and people decide.
DPO as a named role
Your data protection officer has their own role, matrix and signature on every release.
Field-level denies
Hide diagnoses, notes or identifiers from roles that don't need them, down to own-records-only.
Incident tracking
Clinical safety incidents, reviews and corrective actions are managed in the same project.
Evidence on demand
EU AI Act, ISO/IEC 42001 and GDPR mappings, plus your own clinical governance framework.
AI can propose. People decide. In @Human, AI can prepare work but can never approve or publish a release.
Cheaper to run. Impossible to lock in.
@Human favours tested, programmatic automation wherever the choice exists, so your apps cost less, behave the same every time, and keep working without AI.
Lower token costs
Chasing, reminders, rota checks and routing run as automation. AI is reserved for summarising and suggesting.
Care continues offline from AI
If the model provider is down, referrals, rosters and records keep working.
Safe changes
Every change raises an impact review, so a new field never quietly creates a new data risk.
Reusable across trusts
Data models, policies and risk scenarios carry from one service to the next.
Can @Human process special-category health data?
@Human is designed to govern it: the register records categories, purposes, locations, retention and recipients, and field-level permissions restrict access. Your organisation remains the controller.
Does AI make clinical decisions?
No. In @Human, AI can draft and suggest, but approval gates and roles ensure a clinician makes and records the decision.
Where does patient data live?
In your own infrastructure. @Human is customer-run software, not SaaS.
Can we use our own AI model?
Yes. Use any provider, including EU-hosted or open models on your own servers, or none at all.
