MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop
The article introduces MADP, a multi-agent pipeline designed to automate document processing in enterprise environments. It combines deep learning and human validation to enhance accuracy and efficiency, achieving a 97% automation rate in real-world applications. The system also demonstrates significant sustainability benefits, reducing CO2 emissions and resource consumption compared to traditional methods.
- ▪MADP integrates five specialized agents to automate document processing.
- ▪The system achieved a 97.0% full-pipeline automation rate with only 3% requiring non-AI fallback.
- ▪It reduces CO2 emissions by 69%, energy consumption by 69%, and water usage by 63% compared to manual processing.
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Computer Science > Artificial Intelligence arXiv:2605.17159 (cs) [Submitted on 16 May 2026] Title:MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop Authors:Diego Gosmar, Giovanni Zenezini View a PDF of the paper titled MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop, by Diego Gosmar and 1 other authors View PDF HTML (experimental) Abstract:Document processing automation remains a critical challenge in enterprise environments, where traditional manual approaches are labor-intensive and error-prone.
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