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Turn referral records into EHR-ready context.

Husn reads fragmented referral material, including scanned letters, external records, faxes, and emails, extracts what's clinically relevant, matches it to the right patient, and prepares a structured summary for clinician review.

A walkthrough of how Husn reads, matches, and flags a referral for review.

Built for clinicians managing referred-patient caseloads.

01Clinicians reviewing referrals02Referral & care coordination teams03Hospital digital & informatics leaders04Specialty practices & clinics
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One place for every referral source.

Husn reads scanned letters, external records, faxes, and emails, and structures what matters for review inside your EHR workflow.

Ask about any referred patient.

Skip the digging through scanned PDFs and prior notes. Ask a question and Husn answers from what's already been extracted, with every fact traceable to its source.

RCAsk Husn · Riverside ClinicRead-only
What's J. Whitfield's cardiac and medication history ahead of his 2pm review?
Husn

No prior cardiac diagnoses noted in the referral letter or GP summary. Current medications: none listed as ongoing. A short course of antibiotics was prescribed 3 months ago for an unrelated infection, per the GP summary.

Referral letterGP summary
Answers are compiled from documents on file, for clinician review, not a diagnosis.

How it works.

01

Read

Husn reads referral letters, scanned records, and external documents as they arrive.

02

Extract & match

Clinically relevant information is extracted and matched to the correct patient.

03

Review

You get a structured summary, ready for clinician review before anything is added to the chart.

A clinician stays in the loop at every step.

Built by people who've sat with the problem.

Grounded in 40+ interviews with clinicians across the US and UK, and conversations with hospital digital leadership: validation research and pilot interest.

UB
Usman Bawany
Co-founder, Engineering

MSc, University College London, with published research on explainable AI in healthcare. Focused on making clinical information usable and trustworthy.

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LH
Lamaan Haq
Co-founder, Product & Clinical Partnerships

Saw this problem firsthand working across a lab and clinic affiliated with Harvard Medical School and Mass General Brigham, where patient information was trapped in scanned PDFs, referral letters, and external records.

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Pricing depends on deployment scope.

We're shaping pricing around early conversations with pilot-interested doctors. The fastest way to see numbers for your team is a quick call.

See Husn on a real referral scenario.

We'll walk through how Husn reads a referral, extracts what matters, and prepares it for review, and talk through what a pilot could look like for your team.