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Most AI agents that touch legal workflows are stitched together with scraped data, ad-hoc PDFs, and a hope that the LLM figures out the rest. That breaks in production. This post covers what Law MCP is, why consistent schemas matter for legal tool-calling, and how it replaces the retrieval infrastructure every legal AI team is currently rebuilding from scratch.
Thursday, March 12, 2026
March 12, 2026
Unit tests for legal AI: why your agent needs a CI eval pipeline
Legal AI degrades silently. MicroEvals adds fast, repeatable behavioral tests to your CI pipeline so citation failures, hallucinations, and clause drift get caught before production.
Why "chat with PDF" breaks for legal documents — and how we fixed it
Generic PDF chat tools fail legal workflows because they cannot cite sources, handle linked documents, or do exact-phrase retrieval. Here is how LexReviewer solves each of those problems.
Every metric that matters when evaluating a legal AI system
A complete guide to legal AI evaluation metrics — faithfulness, citation accuracy, clause coverage, hallucination rate, and more. Understand what each measures, when it matters, and how to use them together.