Document Intelligence Agent
Extracts structured data from documents and knows how sure it is.
An intelligent document processing agent that reads PDF and Word (DOCX) documents and extracts the required information into clean, structured data. A built-in evaluation system scores every extracted field with a confidence level, so reliable results flow straight through while uncertain ones are routed for human review.
The challenge
Documents arrive as PDFs and Word files in endless layouts. Extraction models can be confidently wrong, and in business workflows a single wrong amount, date or reference number can cost more than having no automation at all.
The approach
I paired an AI extraction agent with a dedicated evaluation layer. Every field is grounded against the source text, checked with format and business rules, and cross-verified to produce a confidence score. Configurable thresholds then decide whether a value is auto-accepted, spot-checked or escalated to a human-in-the-loop review queue.
The result
Teams get the speed of automation with measurable trust: high-confidence data is processed instantly, review effort is concentrated only where it is needed, and every value is traceable back to the exact place it came from in the source document.
Key features
Schema-Driven Extraction
Turns PDF and Word documents in any layout into clean, structured data that matches a defined schema.
Confidence Scoring
An evaluation system validates each field and assigns a confidence level based on grounding, rules and consistency checks.
Human-in-the-Loop Routing
Thresholds decide what is auto-accepted and what is escalated for review, with the source evidence highlighted.