OCR is uncertain about a dossier number; a reviewer checks the source region, records a reasoned correction and sends it to QC.
Trusted Records · Platform
AI/OCR and human review
Turn images into searchable data, with human decisions when confidence or business rules are insufficient.
Inputs and starting conditions
Suitable-quality images, language/document type, metadata schema, file plan and model version.
Workflow and control gates
- 01Assess images
- 02OCR / extract
- 03Classify dossier
- 04Review fields
- 05Send to QC
Retain extracted values with image locations, confidence and model/version. Agree thresholds per record class in the pilot. Independent QC checks reviewed results.
Exceptions and recovery
Low confidence, rule conflicts or AI timeout create review work. Reviewers record reasons for corrections; OCR is not authenticity evidence and AI cannot authorize destruction or lift holds.
Roles, outputs and states
| Responsibilities | Evidence and states |
|---|---|
| Business reviewers confirm fields/classification; AI administrators approve profiles/models; QC checks independently. The owner defines permitted processing. | Source images, original/corrected AI results, reviewer, model/version and decision audit. States: review pending → reviewed → QC; unresolved conflicts remain pending. |
Scenario and acceptance criteria
Complete only when
The final value retains its source image, processing version and reviewer.
Interfaces for this workflow
Integration handoff
End-to-end integration workflows
Connect technical states to business decisions instead of merely listing endpoints.
Read detailsOpenAPI and Swagger Reference
The proposed contract is rendered from one local specification; no network Try-It or real credentials.
Read detailsErrors and next actions
A consistent error envelope guides recovery without disclosing sensitive data.
Read detailsContinue the workflow
QC and output quality
Verify completeness, image quality and metadata before acceptance.
Read detailsTwo journeys, one records lifecycle
Connect paper and born-digital records through persistent identifiers, policies and evidence.
Read detailsIntegration quickstart
Exercise ingest → job tracking → registration → verification with synthetic data.
Read detailsStart with a verifiable scope.
Agree record classes, quality criteria, permissions and evidence before scaling.
Plan assessment