Healthcare & Life Sciences
Clinical staff spend a large part of the day on documentation, coding and correspondence rather than on patients. That is where we work: systems that extract, draft and route the administrative load, with a clinician reviewing anything that touches care.
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Our Solutions
Typical work in this sector
The systems we are most often asked to build in healthcare & life sciences.
Extraction pipelines for referrals, discharge summaries and lab reports, with confidence scores and a review queue
Retrieval over clinical protocols that cites the source passage for every answer
Assistants that draft correspondence for approval rather than sending it
Scheduling and inventory forecasting built on your own history
What we would tell you first
Healthcare is the clearest case for stopping automation short of the decision. We build systems that extract, prepare and draft, and leave clinical judgement — and accountability — with the clinician. Anything else fails the first serious audit, and deserves to.
Healthcare & Life Sciences Technology — Frequently Asked Questions
Where should AI stop in a clinical setting?+
Short of the decision. We build systems that extract, draft and prepare — pulling structured data out of referrals and discharge summaries, drafting correspondence, surfacing the relevant protocol — and leave the clinical judgement with the clinician who is accountable for it. Anything that quietly automates a care decision fails the first serious audit, and should.
How do you handle patient data in an AI system?+
By deciding first whether it needs to leave your estate at all. Where it does not, we use models you host. Where an external model is genuinely better, we minimise what is sent, strip identifiers where the task allows, and make the retention and residency terms of that provider an explicit part of the design rather than a footnote. Consent, retention limits and an access trail are built in, not added at review.
What is the fastest thing to automate in a hospital?+
Usually document work — referrals, discharge summaries, insurance paperwork — because the task is repetitive, the accuracy bar is a tired human at the end of a shift, and a review queue makes the failure mode safe. It is unglamorous next to diagnostic AI, and it returns time to clinical staff considerably faster.
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