Back to the discharge queue
Meena Iyer, claim C-104
What this demo claim shows: The day-3 ICU note is in hospital systems but not in the file. Age 67 triggers a 10% co-pay (C5.4).
Not run yet
1. Claim file
Synthetic patient and documentsInsurer and policy
Sahyog General Insurance (fictional), Arogya Shield Plus, sum insured Rs 5,00,000
Policy since
2017-11-02
Room
General ward, Rs 4,500 a day for 2 days; ICU Rs 9,000 a day for 3 days
Desk note
ICU stay, senior citizen
Documents in the file
2. Bill lines and evidence
Not checked yet| Line | Description and code | Amount | Evidence |
|---|---|---|---|
| L1 | Medical ICU, 3 days ICU-MED | Rs 27,000 | Not checked |
| L2 | General ward, 2 days ROOM-GW | Rs 9,000 | Not checked |
| L3 | CT chest RAD-CT-CHEST | Rs 6,500 | Not checked |
| L4 | ABG, CBC, cultures LAB-ABG-CBC | Rs 4,300 | Not checked |
| L5 | Pharmacy (itemised) PHA-IP-221 | Rs 38,600 | Not checked |
| L6 | Physician and intensivist visits PRF-VISIT | Rs 7,500 | Not checked |
3. Policy checks
Deterministic rules engine, not the language modelThe rules run when the agent calls the policy tool. Each result cites the clause it comes from.
4. Agent trace
0 tool callsLLM planner, gpt-4.1-miniThis deployment has a model configured. The language model will choose each tool call; you will see its reasoning notes.
Press Run the agent. Every card is a real tool call with its input and output; nothing is pre-recorded.
7. Messages with the insurer
Hospital and insurer go back and forth here until the claim is approved or rejectedLoading the conversation.