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.