idp-workflow

Automating PDF document processing with human-in-the-loop validation requires a multi-step pipeline that extracts, classifies, and compares data before human review. This Skill orchestrates Azure Document Intelligence and DSPy LLMs for dual extraction, enabling side-by-side comparison for dispute resolution.

Extracting structured data from loan applications using AI involves classifying the document and applying dual AI extraction. This Skill orchestrates Azure Document Intelligence and DSPy to compare extracted information against rules and uses AI reasoning to validate data with human oversight.

Yes, you need Azure OpenAI and DSPy to build this document intelligence workflow. The pipeline requires Azure Document Intelligence for initial PDF extraction, DSPy for LLM reasoning, Azure Durable Functions for orchestration, and Azure Storage Blob for data handling.

Dual AI extraction improves document data accuracy by independently capturing information and comparing the results. This pipeline uses Azure Document Intelligence alongside DSPy LLMs, triggering human review for side-by-side validation and dispute resolution when discrepancies occur.

Yes, you can use Azure Durable Functions for multi-step document classification and extraction. This Skill leverages Durable Functions to orchestrate the end-to-end workflow, managing the sequence from PDF upload and classification to dual AI extraction, comparison, and reasoning.

You should add human review to an automated document processing pipeline when resolving disputes between dual AI extraction results or validating high-stakes data like loan applications. This Skill provides side-by-side comparison capabilities within the workflow for human-in-the-loop oversight.