@Human for Healthcare and social care

@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
Referral Triage board and My Clinic patient app built on @Human

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.

Article 9

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.

High-risk

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.

DPO scrutiny

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.

Apps 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, an example clinical triage board app built on @Human
Clinical triage board

Referral Triage

Referrals arrive sorted by urgency, with missing information chased automatically by rule. An assistant suggests a priority, and a clinician confirms it.

Clinicians approve every triage, and the suggestion and decision are logged side by side.
Ward Rostering, an example workforce and rostering app built on @Human
Workforce and rostering

Ward Rostering

Shifts, attendance, leave and corrections for every ward, with decisions surfaced to the right manager.

A tested automation checks night-work consent every time the roster changes. No tokens needed.
My Clinic, an example patient assistant app built on @Human
Patient assistant

My Clinic

Patients check appointments and ask everyday questions. Anything clinical is flagged straight to the care team.

Health data stays in the hospital's own infrastructure, and the privacy notice is versioned.

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.

Your questions, answered

Straight answers on governance, data and cost.

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.

See @Human inside your own AI systems

A 20-minute walkthrough for health and care. Bring one AI system you are unsure about. We will show you how it would be classified, logged and reported for EU AI Act compliance inside @Human.