Snowflake launches AI agent governance layer to track activity, control costs
That control plane, according to analysts, could help enterprises address “a real gap” as they scale agentic deployments.
“Most enterprises cannot see or govern agent activity consistently across models, tools, MCP servers, and enterprise systems, as most AI gateways just route models and log prompts,” said Michael Leone, principal analyst, Moor Insights and Strategy.
“Enterprises need to know which agent acted, who authorized it, what resources it used, and what happened at each step. Without that runtime evidence, firms cannot reliably secure, audit, or contain agentic workflows,” echoed Stephanie Walter, practice lead of AI stack at HyperFRAME Research.
