Starburst announced at AI & Datanova, a new set of capabilities designed to operationalize the Agentic Workforce—a paradigm where humans and AI agents collaborate seamlessly across workflows to reason, decide, and act faster and with confidence. With new, built-in support for model-to-data architectures, multi-agent interoperability, and an open vector store on Iceberg, Starburst delivers the first lakehouse platform that empowers AI agents, with unified enterprise data, governed data products, and metadata, empowering humans and AI to reason, act, and decide faster while ensuring trust and control. To further strengthen enterprise confidence in AI, Starburst is introducing advanced observability and visualization features for its agent framework. Organizations can now monitor usage of LLM interactions, set guardrails with usage limits, and view activity through intuitive dashboards. In addition, Starburst’s agent can visualize responses into charts and graphs giving teams not only accurate answers but also clear, actionable insights. These capabilities provide a new level of transparency, governance, and usability as enterprises scale AI adoption. Starburst’s new AI capabilities are built upon the core principle of flexibility, giving organizations the freedom to choose between model-to-data and data-to-model architectures. This approach enables enterprises to scale AI securely, while preserving sovereignty, reducing infrastructure costs, and ensuring compliance. These enhancements include: Multi-Agent Ready Infrastructure: A new MCP server and agent API allows enterprises to create, manage, and orchestrate multiple AI agents along-side the Starburst agent. This enables customers to develop multi-agent and AI application solutions that are geared to complete tasks of growing complexity. Open & Interoperable Vector Access: Starburst unifies access to vector stores, enabling retrieval augmented generation (RAG) and search tasks across Iceberg, PostgreSQL + PGVector, Elasticsearch and more. Enterprises gain flexibility to choose the right vector solution for each workload without lock-in or fragmentation. Model Usage Monitoring & Control: Starburst offers enterprise-grade AI model monitoring and governance. Teams can track, audit, and control AI usage across agents and workloads with dashboards, preventing cost overruns and ensuring compliance for confident, scalable AI adoption. Deeper Insights & Visualization: An extension of Starburst’s conversational analytics agent enables users to ask questions across different data product domains and provide back a natural language response in natural language, a visualization, or combination of the two. The agent is able to understand the user intent and question to do data discovery to find the right data before query processing to answer the question.