Why the data layer decides whether legal AI can be trusted

Every firm is experimenting with AI assistants, agents and in-house tools. Often the weak point isn’t the model, it’s the data behind it. Without a reliable source, AI invents citations, misses unpublished decisions and can’t tell whether a ruling still stands. In this session, we look at legal AI from the bottom up: the data layer. What makes legal data trustworthy, why provenance and legal status matter more than the size of the model, and how law firms and legal departments can connect their own tools to verified sources instead of the open web. You’ll take away: ✔️ Why grounding AI in verified legal data is key to reliable results ✔️ A checklist for judging legal data sources: coverage, provenance, legal status, hosting ✔️ How open standards like MCP let you plug trusted data into the assistants you already use ✔️ When to build and when to buy, and where to start ✔️ A first look at the Pandektes API, launching in 2027