Law firms have moved fast on AI. Document-level tools now read, summarize, compare, and draft to a high standard, and adoption budgets have followed. Yet on the measure that matters most to a transactional practice, whether deals actually run more efficiently, the results have been thin.

The gap isn’t about model quality. Legal AI works at the document level, while deals happen at the transaction level. What closes that gap is infrastructure: a structured, governed environment where the transaction itself lives, which AI tools can read and act on.

Our new whitepaper, Transaction infrastructure for humans and AI, sets out what that layer needs to look like. Inside:

• The five properties a platform needs before it can honestly call itself AI-ready
• A four-layer model of the emerging legal AI stack, from human judgment to stable transaction data
• Why MCP has become the open standard connecting AI agents to real transaction work
• The governance case for architecture over policy, and what each stakeholder gains
• The economic argument for investing in the stable layer while AI budgets are squeezed
• Proof that this infrastructure is already live, not a future roadmap

Legatics is transaction infrastructure in production today. Download the full paper to see the five-property test for AI-readiness and the questions worth asking before your firm locks into its next AI decision.

CTA button: Download the whitepaper