Document Summary
A legal services firm was buried under the weight of thousands of regulatory documents that needed to be read, interpreted, and summarized by their team of lawyers. The firm sought to harness the power of Large Language Models (LLMs) to automate this labor-intensive task and add value to their services.
Challenge
The sheer volume of regulatory documents was overwhelming for the lawyers, who had to extract complex data points and generate summaries under tight deadlines. The complexity of legal language and the nuances involved in regulatory compliance made it difficult to apply a standard automation solution.
Solution
Our approach was twofold:
- LLMs for Data Extraction: We utilized Large Language Models trained on legal datasets to identify and extract key data points and complex clauses from regulatory documents.
- RAG Pipeline and Specialized Prompts: We implemented a Retriever-Augmented Generation (RAG) pipeline that used specialized prompt templates designed for legal text. This pipeline fetched the most relevant segments of the documents and generated concise summaries.
Result
The implementation of LLMs and a specialized RAG pipeline transformed the client's document review process. Lawyers could now focus on high-level tasks, while the automated system took care of preliminary document summarization. This not only increased the firm's efficiency but also improved the accuracy of their document processing, saving both time and resources.
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