Advanced14 min
Agents for Legal
How to build production agents for contract analysis, compliance checking, legal research, and document review — with the guardrails that regulated environments demand.
Quick Reference
- →Always RAG over canonical legal documents — never rely on the LLM's parametric knowledge for statutes or case law
- →Extract structured data (parties, dates, clauses) with tool calling and Pydantic schemas, not free-form generation
- →Implement deterministic compliance rule checks outside the LLM — use code, not prompts, for binary pass/fail rules
- →Require citations for every legal conclusion; reject outputs without source references
- →Human-in-the-loop is mandatory for any output that could be construed as legal advice
RAG Over Legal Documents
Legal agents live or die by retrieval quality. Contracts, statutes, and case law have precise language where a single word changes meaning. Generic chunking strategies destroy the clause boundaries that lawyers rely on. You need domain-aware chunking that preserves section headers, clause numbers, and cross-references.
Clause-aware chunking for contracts — preserves section boundaries
Embedding model matters
General-purpose embeddings (text-embedding-3-small) underperform on legal text. Fine-tune on your corpus or use a legal-specific model. At minimum, test retrieval accuracy with a legal eval set before going to production.