Pipeline RAG: A Revolution in Insurance PDF Analysis
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An Advancement in PDF Document Analysis
A new RAG (Retrieval-Augmentation-Generation) pipeline is transforming the way PDF documents, particularly auto insurance policies, are analyzed and processed. This innovative system has been tested on a 45-page insurance policy, demonstrating its ability to provide accurate and structured responses.
On page 30 of the document, each line is framed and numbered, making it easier to identify relevant information. For instance, the section concerning pet injuries spans several columns, and the answers to the posed questions can be found precisely in lines 54 and 55.
A Four-Step Process
The pipeline stands out with its four-step approach, which goes well beyond traditional integration and generation methods. Here’s how it works:
- PDF Analysis: Documents are converted into relational tables, incorporating rows, bounding areas, pages, and a reconstructed summary.
- Question Transformation: User questions are converted into typed queries, specifying the intent and form of the expected response, such as a capped amount in dollars.
- Directed Retrieval: An anchoring and routing model filters sections to avoid confusion with similar caps.
- Output Generation: The system produces a "contract" output with typed values, coordinated evidence, and confidence levels.
Adaptability and Reliability
The pipeline is designed to adapt to complex questions, such as lists, breakdowns, and targeted synthesis. With audited intermediate objects and a coherent contract, it offers increased reliability for quality control of documents in real-world contexts.
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