DataLife
LLM Bot

Internal Document Q&A Bot

ClientLegalEdge Partners
IndustryLegal Services
Duration3 weeks

Key Result

60% faster document retrieval for the legal team

The Challenge

What needed solving

LegalEdge's associates were spending 2–3 hours per day searching through a 15,000-document repository of contracts, precedents, and compliance policies. Keyword search was unreliable — a clause could be phrased dozens of different ways. Senior partners were frustrated that associates were billing clients for search time rather than analysis.

The Solution

How we solved it

I built a private RAG system using LangChain and ChromaDB, ingesting all 15,000 documents with chunk-level metadata tagging (document type, date, jurisdiction). Associates query the bot in plain English — it retrieves the top-5 relevant passages with source citations, and drafts a structured summary. The system runs entirely on LegalEdge's private cloud with no data leaving their environment, satisfying their data security policy.

Results

The numbers tell the story

60%

Faster average document retrieval time

15K

Documents indexed with metadata

2.5 hrs

Associate time saved daily per lawyer

0

Documents leave the private environment

Tech Stack

Tools used on this project

LangChainChromaDBGPT-4oPythonFastAPINext.jsPostgreSQL
The bot handles document research with a precision our keyword search never could. Associates are billing for analysis, not for searching. It paid for itself within the first billing cycle.

Richard Asante

Managing Partner, LegalEdge Partners

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