An agent crew formy dad's real clinic.

My dad is a doctor. His handwritten prescriptions used to wait weeks to be typed into his 20-year-old patient software. Now five agents plan, retrieve, call tools, and decide - every LLM workload on Vultr Serverless Inference.

PPatient Information System
RegNoFirstNameLastNameAgeGenderAddressFirstVisit
1001APPDEMOONEPATIENT31MVULTR DEMO 104/07/2026
1002APPDEMOTWOPATIENT42FVULTR DEMO 204/07/2026
1003DEMOUSER50FQA ENVIRONMENT04/07/2026
1004CHECKONLY19MSYNTHETIC DATA04/07/2026
1005ALPHAENTRY42FTEST FACILITY04/07/2026
1006BETAENTRY31MTEST FACILITY04/07/2026
Vultr connectedDemo data onlyApproved jobs only
GUARDRAILSApproved cloud jobsAutomatic backupTransaction protectedDuplicate safe
Workflow Manager4 steps
HOW IT WORKS

A multi-step workflow, not a single call.

Every script runs through the full crew - perception, live retrieval, document grounding, and a final decision - through an API bridge we patched into the clinic's real 20-year-old PIS.

01READY

Perception

Vision OCR reads the doctor's handwriting, with alternates for every ambiguous digit - because his 2s look like 9s.

02READY

Live retrieval

The records agent queries the clinic's live patient database in real time, retrying variants until the identity checks out.

03READY

Grounded decisions

Every medicine is cited against a homeopathy remedy corpus via VultronRetriever rerank - no citation, no entry.

04READY

Human-approved outcome

An assistant swipes to approve, and one click inside PIS files the whole batch into the patient records.

SECURITY SETTINGS

Evidence in, entries out.

No value is ever invented - every field traces to OCR evidence, a live database record, or a corpus citation, and a human signs off before anything touches twenty years of patient history.

Try it on a script
Protection status