C. Vertical AI apps
Clinical-scribe note storage
A medical scribe agent transcribes doctor-patient visits and stores structured SOAP notes per encounter with auditable history.
Prompt for any LLM (no setup needed)
Paste this into ChatGPT, Claude, or Gemini — no MCP, no API key, no install:
Read https://instanode.dev/llms.txt for the API.I want to: a medical scribe agent transcribes doctor-patient visits and stores structured SOAP notes per encounter with auditable history.
Write a complete runnable script (bash + whatever language fits) that: - Provisions the services I need (Postgres + S3-compatible storage) from instanode.dev - Does the work above end-to-end - Prints expected output at each step - Tells me how to claim the resources at the end if I want to keep them past 24 hours
Use real curl commands against api.instanode.dev. Quote the actual response shapes from llms.txt. ```
Sample agent prompt
You're a clinical-scribe agent transcribing doctor-patient visits. For each visit, store structured SOAP fields (Subjective, Objective, Assessment, Plan) in Postgres for queryability, and the raw audio + full transcript blob in S3-compatible storage for audit. Every edit creates a new version row — never overwrite.Steps to follow
- Step 1: Provision PG + bucket.
``bash
PG=$(curl -sX POST https://api.instanode.dev/db/new -H 'Content-Type: application/json' -d '{"name":"clinical-scribe-note-storage-db"}' -H "Authorization: Bearer $T" | jq -r .connection_url)
curl -sX POST https://api.instanode.dev/storage/new -H 'Content-Type: application/json' -d '{"name":"clinical-scribe-note-storage-storage"}' -H "Authorization: Bearer $T" > s3.json
``
- Step 2: Versioned SOAP table.
``sql
CREATE TABLE soap_notes (
note_id uuid NOT NULL,
version int NOT NULL,
encounter_id uuid NOT NULL,
subjective text, objective text, assessment text, plan text,
audio_key text, transcript_key text,
authored_by text NOT NULL,
authored_at timestamptz DEFAULT now(),
PRIMARY KEY (note_id, version)
);
CREATE INDEX idx_encounter ON soap_notes (encounter_id, version DESC);
``
- Step 3: Upload raw audio + transcript, insert metadata.
``python
audio_key = f"audio/{encounter_id}.opus"
tx_key = f"transcripts/{encounter_id}.json"
s3.put_object(Bucket="instant-shared", Key=audio_key, Body=audio_bytes)
s3.put_object(Bucket="instant-shared", Key=tx_key, Body=json.dumps(transcript))
pg.execute("""INSERT INTO soap_notes (note_id,version,encounter_id,
subjective,objective,assessment,plan,audio_key,transcript_key,authored_by)
VALUES (%s,1,%s,%s,%s,%s,%s,%s,%s,%s)""",
(nid, encounter_id, S, O, A, P, audio_key, tx_key, "scribe-v3"))
``
- Step 4: Latest version of a note.
``sql
SELECT * FROM soap_notes WHERE note_id = $1 ORDER BY version DESC LIMIT 1;
``
Why this works on instanode.dev
Clinical data needs strict auditability — every edit visible, raw artifacts untouched. Versioned PG rows + immutable objects in S3-compatible storage give that without a custom CDC pipeline. Both resources encrypt at rest by default. Two curls; the same setup that's HIPAA-shaped on day one scales without a re-platform when you go from one clinic pilot to a real deployment.
Related cases
- Personal-injury demand letters — another vertical-AI workflow with auditable versioned documents
- Voice-memo capture pipeline — the audio-capture front end that feeds into structured notes
- EHR appointment webhook fan-in — the upstream event source that triggers a scribe session