AI agents for healthcare.
In healthcare the limit on AI is consequence, not capability. iLeaf builds agents that take administrative and routing load off clinicians while leaving every clinical judgement with a person — including a platform that reduced specialist misrouting by 59% running entirely on a hospital network's own GPUs, with no patient data leaving the premises.
What this looks like in healthcare
- Intake triage
- Agents gather history, flag red-flag symptoms and prepare the case before a clinician opens it.
- Specialist routing
- Matching a presentation to the right specialty first time — the source of the 59% misrouting reduction.
- Record summarisation
- Long EMR histories condensed to what matters for this consultation, with citations back to the record.
- Administrative follow-up
- Appointment chasing, document collection and reminders handled without occupying clinical staff.
Questions we get asked
Can clinical AI run without data leaving our network?
Yes. We have delivered a full agentic stack — retrieval, models and governance — running entirely on a hospital network's own GPUs, with no patient data transmitted externally. Open-weight models make this practical without a meaningful capability trade-off.
Does the agent make clinical decisions?
No. It proposes, evidences and routes; the clinician decides. Every AI-assisted step is recorded with its inputs and reasoning so the decision can be reconstructed later, which is a requirement in clinical settings rather than a feature.
AI & Agents for healthcare — let’s talk.
Tell us what you are running and what it needs to do next. We will tell you honestly whether we are the right team for it.