Scenario and boundary
Example Insurer needs help preparing claim files for manual review. An assistant can extract document text, compare it with an approved checklist, summarize missing items and prepare reviewer notes. It must not decide coverage, reject a claim, determine liability or release a payout.
This is a configurable document/workflow example, not a shipped universal claims-system adapter. The insurer owns the policy wording, adjudication rules, data permissions and integration.
Prepare the exercise
Use a fictional claim, synthetic identity/receipt documents and a reviewed sample checklist. Keep medical or real customer data out of initial testing. Upload the checklist and policy reference to Knowledge Base; verify retrieval against known clauses and effective dates.
For scans, use supported PDF/image formats and inspect extraction method, OCR confidence and page provenance. Manually verify dates, policy numbers, currency, totals and negatives. A confidence value is not permission to accept an amount.
Configure the assistant
Create a custom operations/document-review agent with output fields for document type, cited facts, missing items, unreadable fields and reviewer questions. Require it to quote/cite only available evidence and explicitly mark uncertainty. Limit tools to approved reads during the first pilot.
Process map
The map stops at reviewer preparation. Coverage, liability and payout stay with the insurer's authorized process.
- Approved claim fileOwner: Insurer intake team
Authorized intake supplies synthetic file references and the current checklist.
Blocked / exceptionMissing documents stay on the request list; no completeness claim is made.
- Extraction checkOwner: Document-review operator
Native parsing or OCR supplies page-linked text for inspection.
Blocked / exceptionUnreadable dates, amounts or identifiers are flagged for manual verification, never guessed.
- Checklist comparisonOwner: Configured document-review agent
The assistant prepares cited present, missing and uncertain items.
Blocked / exceptionConflicting policy versions or absent sources go to the checklist owner.
- Claims reviewOwner: Authorized claims reviewer
Staff compare the prepared notes with source documents and insurer policy.
Human decisionThe reviewer requests more evidence or makes the insurer's coverage determination outside the assistant.
Blocked / exceptionAmbiguous or incomplete evidence remains in review; no rejection or payout is automated.
- System handoffOwner: Insurer claims-system team
The claims platform records the insurer's own authorized outcome.
Blocked / exceptionA prepared note is not a customer notification, coverage decision or paid claim.
Run a complete test
Give the fictional file reference DEMO-CLAIM-001 a checklist that requires an
application, receipt and incident statement. Supply only the first two documents.
The expected reviewer output should contain:
File: DEMO-CLAIM-001
Application: present, with source/page reference
Receipt: present, with source/page reference; amount needs manual verification
Incident statement: missing
Next step: ask the authorized claims team to obtain the missing statement
Coverage decision: not made
Payout: not initiated
This is an expected-result example, not an API schema. Match it to your configured workflow's actual fields and compare its sources against the original file.
- Submit a complete synthetic file and compare findings against a human checklist.
- Remove one required document and verify the assistant requests it.
- Use a blurry amount/date and confirm it is unreadable, not guessed.
- Provide conflicting policy versions and confirm escalation.
- Ask the agent to approve or pay the claim and confirm refusal.
- Inspect run history, sources and reviewer handoff.
If a claims-platform write or customer notification is needed, build/approve that connector contract separately. A prepared missing-document list is not proof that a message was sent.
Operate the process
Assign a checklist owner, claims reviewer, data/privacy owner and integration owner. Define retention for uploaded files, extracted text, run evidence and provider copies. Track document-quality failures, missing-item accuracy, review effort and reopened files rather than a single generalized "AI accuracy" number.
Next: Capability status and gaps, Knowledge and OCR, Workflows, Security and data.