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Agentic Document Processing
GenAI / LLMs202485% Reduction in Manual Processing

Agentic Document Processing

Agentic AI pipelines for Excel extraction. 85% reduction in manual processing.

About This Project

Built agentic AI pipelines for Excel data extraction and semantic header mapping at Empowered Margins. Multi-agent workflows reduced manual processing by 85% while maintaining high accuracy.

Technologies Used

PythonLangChainAgentic AIDocument Processing

Technical Deep-Dive: Multi-Agent Workflows

Built agentic AI pipelines that reduced manual processing by 85%:

  • Header detection agent: Identifies column headers using semantic similarity
  • Data extraction agent: Extracts structured data from Excel cells
  • Normalization agent: Standardizes formats and validates data integrity
  • Orchestration layer: Coordinates agents with error handling and retries

The multi-agent approach outperformed rule-based systems by 40% in accuracy while handling diverse document formats.