Select processes where modalities reinforce one another
Examples include receiving goods from a delivery note and photographs, inspecting a site with spoken commentary, triaging a ticket with a screenshot, checking a package against video and paperwork, or drafting meeting minutes linked to source material. If OCR or a deterministic rule solves the task reliably, a complex model is unnecessary.
Define the business output first: a completed record, detected discrepancy, classified incident or draft decision. An elegant description alone is not automation.
Keep the pipeline inspectable
Ingestion, recognition, field extraction, entity linking, interpretation, source verification and action should remain separate and observable. Preserve the page, image region, audio timestamp or video frame supporting every important conclusion.
Validate structured fields against schemas and business rules. Low confidence and contradictions between sources should reach a person instead of being hidden by fluent prose.
Evaluate each modality and the end-to-end process
For documents, measure fields and tables; for images, objects and spatial relationships; for audio, speech, speakers and critical terms; for video, events and time spans. Then evaluate the complete task: was the record correct, the risk detected and the next action appropriate?
The test set should include poor lighting, noise, multiple languages, handwriting, rotated pages, missing materials and deliberately conflicting inputs.
Protect data before connecting a model
Define allowed formats, retention, metadata removal, biometric and personal data, recording rights and processing location. Users should see what is sent to a model, while the audit trail records who received the result and what action followed.
Start with an assistant that produces an evidence-linked draft. Permit automatic action only for a narrow task class with demonstrated accuracy and a safe rollback.