AI OCR Evidence State Machine
Summary
AI and OCR workflows create evidence, not authority. Their state machine makes source artifacts, OCR output, prompt versions, model results, parsing, validation, review, accepted evidence, and correction explicit.
Reader Question
How does model-assisted output become usable operational evidence without letting the model bypass domain validation or human correction?
State Machine
Artifact Captured starts with a document, email, image, portal file, or body text. OCR Extracted creates text or layout evidence. Prompt Prepared records prompt version, model settings, source context, and expected schema. Model Returned captures raw output.
Parsed converts output into typed structure. Validated checks domain rules, citations, confidence, and completeness. Accepted output becomes Evidence Accepted. Ambiguous or invalid output becomes Needs Review. Corrections should become durable training, prompt, rule, or source-context feedback rather than invisible manual cleanup.
This state machine lets POA, precon, and future document workflows share prompted extraction patterns while keeping domain judgment outside the model.
Visual
The diagram centers validation and review between model output and accepted domain evidence.