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Chen & Associates · AI Agents

Legal RAG pipeline

A retrieval-augmented generation (RAG) system that lets a top-50 law firm search its precedents and contracts in seconds, with every answer linked to its source.

Legal servicesVector DBLLMNext.js
−90%Research time
SecondsPer precedent search
The challenge

What needed to change

Chen & Associates holds a vast archive of case files, contracts and internal memos. Finding the right precedent meant keyword searches across separate systems and hours of reading, much of it carried out by senior lawyers whose time is the firm’s most valuable resource.

Off-the-shelf AI chat tools were not an option. The firm needed answers grounded in its own documents, a citation for every claim, and strict controls over who could see which material.

Our approach

How we delivered it

Step 1

Prepare the archive

We built an ingestion pipeline that extracts text from the firm’s documents, splits it into meaningful passages and tags each with its matter and permissions.

Step 2

Index for meaning

Passages are embedded and stored in a vector database, so searches match legal concepts rather than exact keywords.

Step 3

Ground every answer

The LLM answers only from retrieved passages and cites each source document, so lawyers can verify any statement in one click.

Step 4

Deliver a simple interface

A secure Next.js application gives the legal team a familiar search experience, with access controls that mirror the firm’s existing permissions.

Results

The outcome

  • Legal research time fell by 90%.
  • Relevant precedents are surfaced in seconds rather than hours.
  • Every answer links back to its source documents, so lawyers can verify before they rely on it.
  • Senior lawyers spend less time searching and more time advising clients.
“The RAG pipeline they deployed for our legal team is flawless. It’s like having a senior partner who has memorized every contract we’ve ever signed.”
DC
David ChenManaging Partner, Chen & Associates
Stack

Built with

Next.jsPythonLangChainMilvusOpenAIPostgreSQL
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