Nutanix has announced the general availability of Nutanix Agent Gateway as part of Nutanix Enterprise AI 2.7. Nutanix Agent Gateway acts as a centralised front door that manages interactions between AI agents, large language models (LLMs), and enterprise tools. It provides AI developers and platform teams with a single control point to govern agent activity, manage access policies, and monitor token consumption across agentic AI deployments.
Integrated with Nutanix Enterprise AI, the solution helps secure interactions between agents, models, and business applications while providing consistent governance across AI environments, whether they rely on frontier models hosted in the public cloud or self-hosted,private models.
As organisations move from AI pilots to production-scale agentic AI deployments, autonomous agents are increasingly interacting with AI models, enterprise applications, and business data to automate complex workflows. This shift introduces new challenges around governance, access security, and the rising costs associated with model usage.
Nutanix Agent Gateway addresses these challenges by centralising token observability across model providers, enabling IT and platform teams to monitor usage, allocate costs, and better control AI spending. This visibility also helps organisations identify workloads that can be shifted to self-hosted models, reducing reliance on external services and helping optimise costs.
Serving as a control layer connecting requestors (AI users and agents) to AI models and Model Context Protocol (MCP) servers, Nutanix Agent Gateway applies access control policies and tool-level filtering across agents. This enables agents to securely access enterprise resources within a governed environment.
Key capabilities of Nutanix Agent Gateway include:
– Nutanix Agent Gateway Governance for MCP: Set granular access control to MCP servers, enabling agents to securely connect to business tools and private data sources
– Unified Observability: Centralise visibility into token usage, MCP server access, and LLM activity
– Audit Logs: Record every MCP request with a comprehensive audit trail for AI governance
– Unified API: Access external provider models and self-hosted models through a single API, allowing developers the freedom to use the right model for the right use case
– Granular Token-Based Rate Limiting: Enforce token quotas and limits centrally that deliver real-time visibility into token usage across every agent and team
Nutanix Agent Gateway enables organisations to apply consistent governance across agentic AI deployments, regardless of whether they rely on public cloud-hosted or self-hosted models. IT teams benefit from unified management of access policies, governance controls, and token consumption across their AI environments.