Cases
A case = 2+ documents connected through transaction/reference entities. An entity group = 2+ documents connected through identity-only entities.
The case detail page is organized into tabs:
| Parameter | Type | Description |
|---|---|---|
| Overview | tab | AI narration, anomaly banner, entity summary cards, and documents grid. |
| Anomalies | tab | Severity filter pills, dismissable anomaly cards, show-dismissed toggle. Advanced mode only. |
| Evidence | tab | Validation badges (colored dots), filter bar (status/document/category/search), group-by-document collapsible sections. |
| Timeline | tab | Chronological event log for the case. |
Cases display an AI-generated case label as the primary title and include anomaly count badges in the header. The label is generated by analyzing the documents and entities in the case to produce a human-readable summary — for example, "ACME Corp Invoice #4521 → PO #8890". You can rename a case manually if the AI label does not capture the right context. Evidence and Timeline tabs support export to MD, CSV, and JSON for offline review or compliance reporting.
Additional case operations: merge multiple cases into one, split a case into separate groups, pin or remove documents from a case, and confirm or reject individual linking edges. Merging is useful when two cases refer to the same real-world transaction but were not connected by the linking pipeline — for example, when a vendor uses slightly different names across documents. Splitting lets you break apart a case that was over-connected by a high-frequency entity value. Edge confirmation and rejection feed back into the linking model, improving future case formation accuracy.
Cases follow a lifecycle: discovered when the linking engine first identifies a cluster, confirmed when a reviewer validates the grouping, active during ongoing work, and resolved when all documents have been reviewed and processed. The lifecycle status is visible on the cases list page and can be updated from the case detail header. Filtering by lifecycle status makes it easy to focus on cases that need attention.
- AI-generated case labels with manual rename option
- Four tabs: Overview, Anomalies (Advanced mode), Evidence, and Timeline
- Merge, split, pin, remove, confirm, and reject operations
- Lifecycle tracking: discovered → confirmed → active → resolved
- Anomaly count badges in the case header for quick triage
- Export Evidence and Timeline to MD, CSV, or JSON
curl -s "https://api.talonic.com/v1/cases?limit=10" \
-H "Authorization: Bearer $TALONIC_API_KEY"
# Response:
# {
# "cases": [
# {
# "id": "case_abc",
# "label": "ACME Corp Invoice #4521 → PO #8890",
# "document_count": 3,
# "anomaly_count": 1,
# "lifecycle": "discovered",
# "created_at": "2025-04-18T10:00:00Z"
# }
# ],
# "total": 42
# }curl -s https://api.talonic.com/v1/cases/case_abc \
-H "Authorization: Bearer $TALONIC_API_KEY"
# Response:
# {
# "id": "case_abc",
# "label": "ACME Corp Invoice #4521 → PO #8890",
# "documents": [
# { "id": "doc_001", "name": "Invoice_4521.pdf", "type": "Invoice" },
# { "id": "doc_003", "name": "PO_8890.pdf", "type": "Purchase Order" },
# { "id": "doc_005", "name": "Contract_ACME.pdf", "type": "Contract" }
# ],
# "entities": [
# { "value": "acme corporation", "category": "identity", "document_count": 3 },
# { "value": "po-2025-8890", "category": "transaction", "document_count": 2 }
# ],
# "anomaly_count": 1,
# "lifecycle": "discovered"
# }Cases are the primary unit of holistic document review. Rather than reviewing documents in isolation, cases let you see all related documents together — an invoice alongside its purchase order and contract. The AI-generated case label gives you immediate context: "ACME Corp Invoice #4521 → PO #8890" tells you at a glance what the case is about. The anomaly count badge in the header lets you prioritize cases that need attention, and the lifecycle tracking ensures nothing falls through the cracks as your team processes the queue.