Legal AI governance for law firms

A firm may have rules for confidential matters, client restrictions, public AI tools, approved models, retention, research sources and human review. Governance is stronger when those requirements become system settings rather than relying on training alone.

The legal team and security team should be able to explain which policy applied to a particular answer or agent action after the fact.

Ethical walls, client teams and matter-specific restrictions are normal legal operations. Enterprise AI should inherit those boundaries instead of creating a parallel information layer that is broader than the firm's existing access model.

Sanctum's architecture is designed around matter-scoped access and work history so legal intelligence remains tied to the engagement.

Delegated AI work can be valuable, but the system should distinguish reversible operational actions from changes that affect legal or factual state. High-consequence actions should require professional review or remain staged until a lawyer approves them.

Agent policy should also control external search, document edits, publishing, matter scope and audit so autonomy cannot quietly expand beyond the user's instruction.