Production-grade AI across voice, chat, documents, and vision — delivered, deployed, and operated by our team. Book a walkthrough
Applied AI for Healthcare

Applied AI for healthcare — under clinical oversight, by design.

Clinical documentation assistants, patient-facing triage, and pathway support — each deployed with human-in-the-loop review, provenance on every output, and governance aligned to the frameworks your organisation already operates under. Engineered by a team that treats clinical accountability as a system property, not a disclaimer.

Clinician time returned.

Documentation, correspondence and discharge summaries drafted by AI from the structured and unstructured record, then reviewed and signed by the clinician. Drafting time targets are agreed before deployment and measured in production.

Safer patient pathways.

Triage and prioritisation applied to inbound demand, with every recommendation carrying its source evidence and a clinician-review gate before it changes a patient’s pathway.

Audit-ready by design.

Every model output is logged with its inputs, version, and the clinician decision that followed. Outputs are reproducible; decisions are reviewable; retention is set by your organisation.

Patient-facing assistants, under clinical oversight.

Voice and chat for appointments, prescription enquiries and aftercare. Anything with clinical content is routed to a clinician before reaching the patient; the assistant states its limits explicitly.

How we work in healthcare

Evidence, oversight, and audit — in that order.

We operate healthcare AI the way healthcare itself operates. Four principles are applied to every engagement, checked at review, and visible to the people accountable for the service.

Evidence
Every model we deploy is evaluated against a held-out set drawn from your own records, under your clinical governance, before it is allowed near a live pathway. Performance is reported as the metrics your service already uses — not as aggregate accuracy scores that hide failure modes.
Oversight
No AI output reaches a patient, changes a pathway, or enters the medical record without an identified clinician reviewing it. The review step is part of the system, not adjacent to it.
Audit
Inputs, outputs, model versions and downstream decisions are retained for the period your governance requires. The record is machine-queryable and human-readable; your Caldicott Guardian, DPO and clinical safety officer can see what the system did and why.
Data containment
Patient data stays within your environment and your jurisdiction. It is not used to train models that leave your organisation. Retention and deletion are configured to your policy, not ours.
The rules healthcare runs on.

Healthcare operates under rules that matter. Our trust framework — the operational controls, the regulatory alignment, and the review cadence — is documented in full, and maps directly to the EU AI Act, UK AI principles, GDPR and ISO/IEC 42001.

Review our trust framework
Indicative applications

Where our work fits in a clinical service.

Not a product catalogue. Three shapes of engagement we are set up to deliver, with the same operating principles above applied to each.

Clinical documentation assistants

Ambient and retrospective drafting of notes, letters and discharge summaries. A clinician signs every output; nothing enters the record unreviewed.

Patient triage and aftercare

Voice and chat assistants for routine demand — appointments, prescription enquiries, post-discharge check-ins — with explicit escalation to a clinician for anything clinical.

Imaging and records review support

Prioritisation and pre-read assistance across imaging and longitudinal records. Every finding is clinician-confirmed before it enters the record or changes a pathway.

Speak with our clinical team.

A direct conversation with the engineers and clinicians on our healthcare practice. For procurement and information-governance enquiries, indicate so in your message and we will route it accordingly.