About This Architecture

Azure Document Processing Sequence Flow orchestrates multi-phase document ingestion, extraction, and reporting using SharePoint, Logic Apps, Azure Functions, and AI Search. The workflow triggers from SharePoint, extracts metadata via Logic App, processes files through conditional branching based on Excel tier classification, and evaluates clauses using Azure AI Search and OpenAI LLM integration. Results are persisted to Azure SQL DB and reports generated by a dedicated Azure Function, demonstrating enterprise-grade document automation with decision points for direct indexing versus Function-mediated processing. Fork this diagram to customize tier logic, integrate alternative LLM providers, or adapt the clause evaluation loop for your compliance requirements.

People also ask

How do I build an end-to-end document processing pipeline in Azure that extracts metadata, normalizes files, indexes with AI Search, and evaluates clauses using OpenAI?

This diagram illustrates a four-phase Azure workflow: Phase 1 triggers from SharePoint via Logic App to extract metadata; Phase 2 loops through files with tier-based conditional routing (Tier 1 direct reporting vs. Tier 2/3 normalization); Phase 3 evaluates clauses using Azure AI Search and OpenAI LLM; Phase 4 saves results to Azure SQL DB and generates reports. Sync calls (solid arrows) and async