Vladimir Kolovski

As AI agents move from prototypes to production you need a centralized governance layer for tool access and we uniquely have a way to solve this with Unity AI Gateway. Integrating tools, and MCP servers consistently and safely has become one of the biggest bottlenecks to adoption.In this session, we explore how Model Context Protocol (MCP) and tool gateways redefine how agents interact with the world. MCP standardizes how agents discover and use tools dynamically, while Unity AI Gateway acts as the enterprise control plane to govern access, manage credentials, and monitor usage across every tool and model. Together, they replace fragmented APIs with a unified, governed interface — letting agents securely connect to managed, external, and custom MCP servers and select tools at runtime.Through real architectures, you'll see how to design agent systems that are flexible, interoperable, and production-ready across internal data and third-party systems.

Whether you're using OpenAI, Anthropic or open-source models like Meta Llama, the Mosaic AI Gateway is the central control plane across any AI model or agent. Learn how you can streamline access controls, enforce guardrails for compliance, ensure an audit trail and monitor costs across providers — without slowing down innovation. Lastly, we’ll dive even deeper into how AI Gateway works with Unity Catalog to deliver a full governance story for your end-to-end AI agents across models, tools and data. Key takeaways: - Centrally manage governance and observability across any LLM (proprietary or open-source) - Give developers a unified query interface to swap, experiment and A/B test across models - Attribute costs and usage to teams for better visibility and chargebacks - Enforce enterprise-grade compliance with guardrails and payload logging - Ensure production reliability with load balancing and fallbacks