1 Clinical Documentation AI Agent, Live in Production.

1 live agent automates clinical documentation within healthcare. It runs on demand. It publishes the inputs it needs, the steps it works through and what it hands back.

  • Live

    Clinical Document Summary

    Summarise a discharge summary, consultation note, or referral letter, and emit the problems, medications, and follow-up actions as a structured FHIR bundle alongside the readable version.

Emitting a structured bundle alongside the readable version, not instead of it

Clinical correspondence carries structured information inside unstructured prose. A discharge summary states the problems, the medications on discharge and the follow-up actions required, and all of it arrives as narrative — so it has to be read and re-keyed into the record by someone, or it is not in the record at all. The re-keying is where information is lost, and the loss is invisible: a medication change mentioned in a paragraph rather than a list, a follow-up action attached to a condition, an allergy noted in passing. Structured extraction is the obvious answer and carries an obvious risk, which is that a structured output looks authoritative regardless of whether the extraction was correct.

Clinical Document Summary summarises a discharge summary, consultation note or referral letter and emits the problems, medications and follow-up actions as a structured FHIR bundle alongside the readable version. The word alongside is doing the work. A structured bundle on its own is unverifiable in practice — nobody re-reads the source to check it, so an extraction error becomes a record error. Producing both means the clinician reviewing it can see what the document said and what was extracted from it in the same place. One agent covers this process, it does not alter a record, and its output is for clinical review before anything is filed.

What this moves

Structured data available from narrative documents
Problems, medications and follow-up actions are emitted as a FHIR bundle, so information locked in prose becomes usable by the record system.
Extractions that can be checked
The readable summary is produced alongside the structured output, so a clinician can verify the extraction against the source rather than trusting it.

Healthcare

How AI agents handle clinical documentation

Drawn from the 1 agent above — what they require, how they run, and what comes back.

What they need

  • Clinical document
  • Summary settings

What comes back

  • Encounter Metadata grid
  • Summary Written summary
  • Problems and diagnoses Table of results
  • Medications Table of results
  • Follow-up actions Verification checklist
  • Needs attention Flagged exceptions
  • FHIR R4 bundle Json payload

How they run

Run on demand
1
Steps per run
4
Credits per run
6

Where clinical documentation fits in healthcare

Documentation takes a large share of every shift and is a leading reason people leave. Drafting it from the record is where the time comes back.

All 3 healthcare agents

Next Step

Deploying clinical documentation agents

These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.

Book a Technical Call
  • No sales script
  • NDA on request
  • Scoping notes sent within 48 hours
Call us Book a call