CLFeb 26

IDP Accelerator: Agentic Document Intelligence from Extraction to Compliance Validation

Amazon
arXiv:2602.23481v11 citationsh-index: 13Has Code
Originality Highly original
AI Analysis

This work provides a more robust and efficient solution for intelligent document processing, benefiting industries that handle complex document packets and require strict compliance validation, such as healthcare.

This paper addresses the challenge of extracting structured insights from unstructured documents, particularly multi-document packets and complex reasoning tasks. The IDP Accelerator framework, utilizing agentic AI, achieved 98% classification accuracy, 80% reduced processing latency, and 77% lower operational costs in a production deployment at a healthcare provider.

Understanding and extracting structured insights from unstructured documents remains a foundational challenge in industrial NLP. While Large Language Models (LLMs) enable zero-shot extraction, traditional pipelines often fail to handle multi-document packets, complex reasoning, and strict compliance requirements. We present IDP (Intelligent Document Processing) Accelerator, a framework enabling agentic AI for end-to-end document intelligence with four key components: (1) DocSplit, a novel benchmark dataset and multimodal classifier using BIO tagging to segment complex document packets; (2) configurable Extraction Module leveraging multimodal LLMs to transform unstructured content into structured data; (3) Agentic Analytics Module, compliant with the Model Context Protocol (MCP) providing data access through secure, sandboxed code execution; and (4) Rule Validation Module replacing deterministic engines with LLM-driven logic for complex compliance checks. The interactive demonstration enables users to upload document packets, visualize classification results, and explore extracted data through an intuitive web interface. We demonstrate effectiveness across industries, highlighting a production deployment at a leading healthcare provider achieving 98% classification accuracy, 80% reduced processing latency, and 77% lower operational costs over legacy baselines. IDP Accelerator is open-sourced with a live demonstration available to the community.

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