Production NLP for clinical documents, trial-matching, prior-authorisation, and structured patient records — mapped to SNOMED CT / ICD-10, NHS IG-aware, MHRA-ready when the system is a medical device.
Most healthtech and clinical-ops teams we work with have the same three problems — and adding analysts has stopped being a viable answer.
GP correspondence, discharge summaries, scanned referrals — the data is in there, but it is in 12 formats, 4 languages, and bound by NHS Information Governance rules.
Eligibility checks done by hand against 200+ medical entities, with a delay measured in days. Patients miss their trial windows because of operational latency, not clinical eligibility.
MHRA Software-as-a-Medical-Device, the EU AI Act's high-risk classification for health, NHS DSP toolkit, and the AI Safety Institute — all stacking into a single sign-off your second-line cannot wave through.
We ship one tightly-scoped clinical AI engagement at a time, in 6 to 10 weeks, with documentation built for MHRA / NHS DSPT / EU AI Act audits.
A representative view of the clinical NLP & trial-matching engine we ship for healthtechs and NHS trusts. Click between tabs, switch languages — everything in here is built to work in your clinicians’ and patients’ language.
| Entity | SNOMED CT | ICD-10 | RxNorm | Conf. | Status |
|---|---|---|---|---|---|
| Hypertension | 38341003 | I10 | — | 0.97 | mapped |
| Type 2 diabetes mellitus | 44054006 | E11 | — | 0.96 | mapped |
| Amlodipine 5mg | 387562000 | — | 197361 | 0.94 | mapped |
| Metformin 1000mg | 372567009 | — | 861007 | 0.93 | mapped |
| Follow-up consultation | 35025007 | — | — | 0.91 | mapped |
| eGFR | 80274001 | — | — | 0.88 | review |
| Field | Value |
|---|---|
| Intended purpose | Decision support · eligibility check · not autonomous diagnosis |
| Intended users | Trial coordinators · clinical research nurses · GP / consultant oversight |
| MHRA class | IIa |
| EU AI Act | High-risk (Annex III · health) |
| Clinical evaluation | N=2,400 · sensitivity 92% · specificity 89% |
| Human oversight | Clinician sign-off required before referral. AI flags only, never auto-refers. |
| Post-market surveillance | Drift alerts · adverse-outcome log · quarterly clinical eval refresh |
| Training data | UK clinical corpus 42k notes · SNOMED CT 2026-04 · bias audit Q3 2025 |
sensitivity 0.92 · specificity 0.89A 30-minute call. We will look at your actual workflow, the regulator you answer to (MHRA / EMA / NHS / ICO), and tell you which clinical AI use case to ship first — and which to defer until the regulatory shape is clearer.
We are not. We deliver clinical AI systems for clients who are (or who need to register as one). Our role is to build, document, and harden the system so your MHRA / EMA submission is straightforward; the placing-on-market and post-market obligations sit with you as the manufacturer.
Yes. We have worked under NHS Information Governance, signed DSPT-aligned DPAs, and deployed on NHS-friendly cloud regions. Data residency stays where you need it.
We do not do clinical evaluation ourselves — that's the manufacturer's clinical-affairs function. We do produce the engineering artefacts the clinical evaluation needs: ground-truth datasets, retrieval / extraction accuracy reports, drift monitoring, and adverse-outcome logging.
Every engagement is scoped after a 30-minute discovery call and a clinical-workflow walk-through. We send a written, fixed-scope proposal — with timeline, clinical and regulatory deliverables, and a transparent quote — within 5 working days.
Book a 30-minute call. We will scope a use case that delivers in weeks, with the audit trail and regulator-ready documentation built in from day one.
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