---
title: "Building A Legal RAG App in 36 Hours"
url: https://daily.dev/posts/building-a-legal-rag-app-in-36-hours-qqj2wt97w
source_url: https://weaviate.io/blog/legal-rag-app
type: article
source: "Weaviate"
published: 2026-02-26T14:31:16.029Z
updated: 2026-02-26T14:31:39.496Z
tags: ["ai-agents", "legal", "rag", "vector-search", "weaviate"]
reading_time: 5
upvotes: 1
comments: 0
language: en
---

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# Building A Legal RAG App in 36 Hours

**[Weaviate](https://daily.dev/sources/weaviate)** · 5 min read · 1 upvotes · 0 comments

## Summary

A walkthrough of building a production-ready legal contract RAG application in 36 hours using Weaviate's Query Agent and Agent Skills library. The architecture uses ColQwen multivector embeddings to encode PDF pages as visual tokens (avoiding OCR/chunking), Muvera compression for efficiency, and three separate Weaviate collections for different contract types. The Query Agent handles agentic search by inspecting schema, constructing structured queries with filters, reranking results, and synthesizing grounded answers. The app supports two modes: Search Mode for discovery and Ask Mode for direct Q&A with cited sources. Setup is demonstrated via a single prompt in Claude Code or Cursor using the CUAD public dataset.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://weaviate.io/blog/legal-rag-app>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#legal](https://daily.dev/tags/legal), [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#weaviate](https://daily.dev/tags/weaviate)

[View this post on daily.dev](https://daily.dev/posts/building-a-legal-rag-app-in-36-hours-qqj2wt97w)