Clinical Staff Spend 30–40% of Their Time on Documentation.
Some of That Can Be Zero.
Patient intake forms, EHR data entry, clinical notes, referral letters, insurance claim documents — every hour a clinician spends on these is an hour they're not with a patient. We build the AI pipelines that handle document processing at 97%+ accuracy, with HL7 FHIR integration and full GDPR compliance — because healthcare records aren't the place to cut corners on either.
documentation & admin tasks
(AMA / JAMIA research)
patient intake pipeline
healthcare document project
What's Actually Draining Healthcare Operations
These aren't edge cases. They're the daily operational reality of clinics, hospital networks, and medical practices across Europe.
Receptionists or admin staff spending hours every day copying data from paper forms, emails, or PDFs into the Electronic Health Record. Field by field. With the attendant transcription errors, missing values, and compliance exposure that manual data entry always creates.
When patient intake forms take 2–3 days to reach the EHR, care coordination is working on incomplete information. Appointments get scheduled with missing allergy data. Referrals go out without complete medication histories. The backlog isn't just an admin problem — it has clinical consequences.
Paper forms in filing drawers, PDFs in email inboxes, scan folders with no access controls. Every record that lives outside an encrypted, audited system is a GDPR exposure. Most clinics haven't fully audited this — the liability is there regardless.
Insurance pre-authorisation requests, referral letters, discharge summaries — each a different format, each requiring manual extraction and entry. This work falls to the same admin staff already handling intake, creating a queue that never clears.
What We Actually Built
From 3-Day Backlog to Same-Day Patient Intake
Receptionists spending hours every day transcribing paper forms, field by field, into the EHR. Errors creeping into patient records. Paper files scattered across the clinic — a GDPR exposure that hadn't been properly audited in months. The system we built accepts handwritten or digital forms, extracts structured data at 97%+ accuracy, validates it against the patient record, and syncs via HL7 FHIR API — the same day.
~7.5 FTE-hours/day of transcription eliminated (€47K) + GDPR risk reduction (€40K) + same-day processing enabling patient throughput gains (€88K). Payback: ~9 weeks.
Healthcare Automation Has Non-Negotiables
Accuracy, compliance, and auditability aren't optional features in healthcare. They're the architecture.
Handles both printed forms and handwritten entries. OCR pre-processing with image enhancement (deskew, contrast normalisation) before extraction — we don't assume clean digital inputs.
Extracted data is validated against FHIR R4 resource schemas before writing to the EHR. Incompatible or low-confidence records go to a review queue — never silently into the patient record.
Every source document is archived in encrypted storage with access logging, retention policies, and deletion workflows. No more PDFs in email or unaudited scan folders.
Extractions below a configurable confidence threshold route to a staff review interface — not to the EHR. The system handles the clearly legible 95%; staff focus only on the genuinely ambiguous.
What We Build On
How many forms does your team process manually each day?
Tell us your intake volume and your EHR platform. We'll tell you exactly what an automation pipeline would look like, with GDPR and compliance already factored in.
Get a scoped estimate