Many enterprise processes begin with a document and end in manual reading, reconciliation, re-entry, and routing. That makes document intelligence a practical entry point for machine-learning and agentic AI—provided extracted data is treated as evidence to validate, not default truth.

Databricks Document Intelligence focuses on extraction from complex documents. The problem is therefore more than OCR: a workflow must turn document content into structured output reliable enough for another system to use.

Separate extraction from the business decision

A safer architecture has at least two layers. One extracts fields, tables, or entities; another checks completeness, format, conflicts, and confidence conditions before data moves further.

An agent can coordinate classification, route selection, and exception handoff. It should not automatically turn an inferred value into an irreversible business-system change without a governing policy.

Design the exception path first

Complex documents produce missing fields, unusual layouts, and conflicting information. A useful pilot does not hide those cases behind an aggregate success rate; it retains the original document, extraction output, routing reason, and reviewer decision.

That record helps teams identify document types suitable for earlier automation and types that still require review. It also provides a basis to improve prompts, rules, and evaluation criteria without sacrificing auditability.

Measure quality by downstream impact

Do not stop at whether an extraction looks plausible. Measure verified-field rate, exception rate, handling time, and defects that reach downstream systems. Those measures connect model capability to operational risk.

In 5 Minutes

• Document intelligence turns complex documents into structured workflow inputs.
• Keep extraction, validation, and business action separate.
• Exception handling needs retained evidence and review decisions.
• Judge quality by downstream defects, not appearance alone.

Sources

• Agentic Data Operations Platform (ADOP): Data engineering into hours
• Connecting retail demand planning to campaign and store execution
• Designing effective Genie Agents from a single prompt
• Databricks Document Intelligence: pushing the frontier for complex document extraction
• When it comes to Governance, Retailers need a control plane for context