Ever struggled with getting AI to work effectively for your specific domain needs? Join us to discover how establishing the right data foundation transforms the way you build and deploy specialized AI agents. This session demonstrates how to prepare and structure your information assets to enable more powerful, efficient AI applications. Learn proven approaches for extracting value from both structured and unstructured data, creating knowledge bases that serve as the backbone for domain-specific agents, and implement optimization techniques that balance quality and resource constraints.Key takeaways: Preparing diverse data sources for AI consumption and knowledge extraction Building scalable data foundations that naturally facilitate agent development Optimizing domain-specific agents for performance and cost efficiency Implementing practical governance frameworks for AI systems built on your data

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