[Proof 02] Tibra Health · Clinical AI

A clinical AI app that drafts the note, not the decision.

An AI scribe writes the visit note while the clinician talks, and the clinician reviews it before anything is saved. A five-week web MVP, now run under a monthly SLA, with the mobile app on its way to the stores.

Web MVP
Live in 5 weeks
Patient data
Kept in the EU
Runs under
A monthly SLA
Web and mobile · visit note
app.••••••.health/visits/3021
Live transcriptREC 06:31
Patient · 02:14The headaches started three days ago. Worse when I wake up.
Clinician · 03:40Blood pressure is 128 over 82. Neck moves freely.
Clinician · 05:02This looks like a tension-type headache.
Clinician · 06:31Drink more water, keep a sleep log, back in two weeks.
Visit noteDraftSaved 10:42
SHeadache for 3 days, worse in the morning.02:14
OBP 128/82. No neck stiffness.03:40
ALikely tension-type headache.05:02
PFluids, sleep log, review in 2 weeks.06:31
AI suggestionICD-11 8A81 · Tension-type headacheAdvisory. Not added until the clinician accepts it.
Main model · backup readyReview and save✓ Reviewed
✓Reviewed by the clinician and saved
10:365G
Visit · Room 3Recording
06:31
The note fills in on the web app while you talk.
Sample visit · no real patient
[01] At a glanceThe build in six lines

At a glance

Client
Tibra Health, a clinical AI company
What we built
An AI scribe, a note editor and PDF reports, then health-record links, red flags and visit summaries
Stack
Next.js with Supabase in the EU on the web, and Expo for iPhone and Android
Time
2025 to 2026, starting with a five-week web MVP
Data and security
Consent before recording, patient data in the EU, and a security brief
How it runs now
Under a monthly SLA, with the mobile app on its way to the stores
[02] The problemBefore the build

Draft the note. Never make the call.

A clinician's notes have to be right, and the decisions in them have to stay the clinician's. So the AI scribe drafts the visit note while the clinician talks, and nothing is saved until the clinician has read, edited and signed it.

It also had to ask the patient for consent before recording, keep patient data in the EU, and reach clinicians fast. The first version went live as a web MVP in five weeks.

[03] The architectureApps, AI, data

Drafted by AI, signed by the clinician.

A web app on Next.js, with Supabase in the EU behind it. The mobile app is built with Expo and is on its way to the stores.

People
CliniciansRecord, edit and sign
PatientsAsked for consent first
Apps
Web appNext.js
Mobile appExpo, on its way
AI and reports
AI scribeDrafts the visit note
Red flagsPhase 2
PDF reportsFrom signed notes
Data
Supabase, EUVisits, notes, consent
Health recordsLinked in phase 2
[04] What we builtPhase by phase

Three parts first, three more next.

The top row went live as the five-week web MVP. The second row is phase 2, planned at six weeks.

AI scribe

Drafts the visit note while the clinician talks, once the patient has agreed to the recording.

Note editor

The clinician reads, edits and signs the draft. Nothing is saved before they do.

PDF reports

Each signed note turned into a PDF report.

Health-record links

Each visit linked to the patient's health records.

Red flags

Warning signs in a visit flagged for the clinician to check.

Visit summaries

A short summary of each visit, drafted for the clinician to review.

[05] The resultFigures from the build

The result

5Weeks from the start of the build to a live web MVP
EUWhere patient data stays, in Supabase's EU region
3Phase 2 modules planned on top of the MVP: health-record links, red flags and visit summaries
[06] How it runs nowA monthly SLA

Live, and run every month.

The web app runs under a monthly SLA, with phase 2 planned on top of the MVP and the mobile app on its way to the App Store and Google Play. We also wrote the app's security brief, and patient data stays in the EU.

[07] Use cases this provesBuild the same for you
[08] Next30 minutes · no slides

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