What agentic extraction means
In Cogneris, agentic document extraction is a controlled workflow pattern. The system classifies the document, selects an extraction strategy, applies a schema, checks evidence, validates business rules, and decides whether the result can move forward or needs review.
Intake
Accept uploads from portals, APIs, inboxes, SFTP drops, or case-management workflows.
Classify
Detect document type, split packets, and choose the extraction route before fields are requested.
Extract
Return typed JSON with confidence, citations, page-level evidence, and schema versions.
Validate
Check totals, dates, required fields, cross-document consistency, and policy rules.
Review
Route only uncertain fields to a human while high-confidence values keep moving.
Handoff
Send approved data to webhooks, portals, CRMs, ERPs, loan systems, or claims platforms.
Document workflow agents
A document workflow agent is useful when extraction is only one step in a longer operating process. It can watch for a new upload, identify what arrived, ask for missing evidence, extract the fields, validate the result, open review tasks, and call the next system once the document is approved.
| Stage | Agent responsibility | Output |
|---|---|---|
| Intake | Collect files and map them to a case, tenant, or checklist. | Document ID, case ID, required-document status. |
| Extraction | Apply the right schema and preserve citations. | Fields, tables, confidence, source evidence. |
| Validation | Run deterministic checks after probabilistic extraction. | Pass, fail, review-required, and error reasons. |
| Decision | Decide whether to auto-approve, request correction, or route review. | Workflow status and reviewer task. |
| Handoff | Notify downstream systems and keep the audit trail intact. | Webhook event, export log, and audit record. |
Where this beats single-pass OCR
Single-pass OCR works for simple text capture. Agentic extraction is a better fit for contracts, claims packets, KYC files, underwriting evidence, and multi-document workflows where the model has to reason about missing fields, conflicting evidence, and review thresholds.
Production requirements
A useful agentic system needs traceability. Cogneris records model versions, prompt hashes, validation rules, source citations, reviewer changes, webhook state, and decision outcomes so the workflow can be debugged later.
What the API returns
Agentic extraction should still return boring, dependable output. Cogneris returns typed JSON with schema versions, per-field confidence, source citations, validation results, reviewer state, and webhook events so developers can connect the workflow without scraping model prose.
| Output | Why teams ask for it | Where it goes next |
|---|---|---|
| Typed JSON | Stable field names and arrays for application code. | Loan systems, AP tools, CRMs, ERPs, portals. |
| Source citations | Reviewers can verify the exact page or bounding box behind a value. | Review queues, audit trails, customer support. |
| Validation state | Probabilistic extraction gets checked by deterministic business rules. | Approval routing, exception handling, webhooks. |
| Trace metadata | Operators can debug model, prompt, schema, reviewer, and export history. | Compliance evidence and production incident review. |
Good fits for workflow agents
Use this pattern for lending portals, KYC onboarding, AP exceptions, claims packets, vendor onboarding, tax intake, and customer document collection. These workflows need more than extraction: they need status, reminders, decision rules, and a durable audit trail.