Request Document Summarization
Challenge: Extensive and time-consuming manual review
Engineers spend multiple hours navigating and analyzing request folders containing hundreds of documents and up to thousands of pages. The heavy reliance on manual document review slows response times and introduces variability. These limitations can propagate into downstream processes, impacting output consistency and operational efficiency.
Solution: Synthesizing and extracting critical information
We developed a custom LLM-enhanced recursive document processing pipeline, capable of handling long document summaries as well as global concept summaries. We leveraged OCR and small-scale LLMs, prioritizing extraction accuracy and response latency.
By identifying the key elements required for document analysis, we were able to design a structured 35-point response template. This template provides an overall view of each folder while also providing references to specific documents or pages for easier review. In addition, we implemented smart title generation for each document, and intermediate summary generation to facilitate navigation and understanding.
As user experience was at the core of this project, we enabled rapid adoption through an ergonomic UI, intelligent referencing through link expanders, clear separation of key topics, and built-in feedback mechanisms.
Business Impact: Processing with higher accuracy and speed
Creating a solution that extracts and structures key information from large document sets enables more efficient and reliable processing, resulting in:
- Improved analysis efficiency, reducing time spent on manual review and information retrieval.
- Higher accuracy and completeness, ensuring critical pieces of information are consistently captured.
- Greater consistency in outputs, with standardized summaries across folders.