Case Study

Laiwyer

Agentic research workflows with grounded retrieval and secure workspaces

Built an agentic legal intelligence platform using LangGraph for query planning, tool usage, retrieval, and citation-grounded response synthesis over multi-source legal data.

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Legal retrieval
RAGLegal retrieval
Grounded answers
CitesGrounded answers
Secure access
RBACSecure access

Stack

  • LangGraph
  • RAG
  • Vector Search
  • RBAC
  • Streaming Chat
The problem

What needed solving

Legal teams needed complex research across statutes, case law, and internal documents without unreliable answers or missing citations.

What we built

The system

Built an agentic legal intelligence platform using LangGraph for query planning, tool usage, retrieval, and citation-grounded response synthesis over multi-source legal data.

  • Before: Manual legal research, scattered documents, limited citation confidence
  • After: Agentic research workflows with grounded retrieval and secure workspaces
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More proof

Other systems we have shipped

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