Every enterprise is building agents. Almost none can account for them.

AI agents require an independent observability and governance layer because infrastructure monitoring and individual platform consoles do not provide a complete enterprise-wide view of agent ownership, costs, performance, or risk. Dataiku Agent Management, planned for general availability in October, is presented as a platform-agnostic supervision layer with three functions: discovering agents across tools such as Copilot Studio, Agentforce, Bedrock, Vertex, Databricks, Snowflake, and n8n; monitoring each agent’s usage, costs, operational health, quality, and behavioral drift; and managing risk through certifications, recurring tests, mitigation requirements, and audit-ready records. The approach is intended to help organizations identify previously unknown agents, distinguish low-use agents from widely adopted ones, detect issues such as changing user requests or declining success rates, and apply stronger controls to agents that handle sensitive data, serve customers, or execute transactions. Rather than operating or enforcing guardrails on agents, the layer records and evaluates their behavior while leaving runtime controls to the platforms where the agents are built and deployed.

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