Azure Extract API
Map document-analysis output into a record your application can validate and govern.
A focused use case
Create a reviewable document workflow that separates source recognition from application-specific field meanings and downstream approval.
A practical workflow
Choose the appropriate Document Intelligence capability, define the field contract, and test representative inputs. Keep permissions, retention, failures, and review decisions visible across the handoff.
An example record contract
These fields illustrate the decisions to make before implementation. Adapt the names and required values to the receiving system; the table is not a promise of a live endpoint or a provider-specific response.
| Example field | Meaning in this contract |
|---|---|
| source_document | Input identity |
| analysis_reference | Processing context |
| normalized_fields | Application contract |
| review_outcome | Accepted or held |
Limits worth keeping visible
A platform feature does not guarantee correctness for every layout. Verify current service capabilities and your own account configuration rather than relying on generic compatibility claims.
Before increasing the workload
Run a small, authorized test set through the whole path, including the receiving application. Keep accepted, rejected, and incomplete outcomes distinguishable. A result should retain the context needed to explain its meaning after it leaves the extractor.
Continue with AI Extract API: A Reviewable Document Workflow for the full implementation discussion, and use the sample contract documentation to review the shape of a handoff.
Consult the source documentation for implementation details and current access conditions. The workflow above is an editorial planning pattern.