At AI & Datanova 2025, Starburst unveiled a major evolution of its data platform aimed at operationalizing what it calls the Agentic Workforce—a model where humans and AI agents collaborate across workflows to reason, decide, and act with confidence. The company says it’s the first lakehouse to unify AI agents, governed data products, and metadata, bridging the gap between generative AI and enterprise-grade governance.

The launch introduces built-in support for model-to-data architectures, multi-agent interoperability, and an open vector store on Iceberg—capabilities designed to give enterprises both speed and control as they scale AI. Starburst’s federated approach allows AI agents to securely access data wherever it resides—on-premises or in the cloud—without copying or moving it, a critical factor for regulated sectors and cross-border operations.

From Data Access to Intelligent Action

For years, enterprises have faced a dilemma between the power of AI and the constraints of governance. Starburst’s update seeks to resolve that by connecting AI models directly to governed data, rather than forcing data to move to the model. This “model-to-data” strategy reduces compliance risk, helps maintain sovereignty, and lowers infrastructure costs.

“With the Agentic Workforce, enterprises move beyond analyzing data to taking intelligent action,” said Justin Borgman, CEO and Co-Founder of Starburst. “Our latest innovations bring models directly to governed data, enable multi-agent interoperability, and open access to vector stores without lock-in—empowering organizations to scale AI securely across clouds and borders.”

Industry analysts see the move as part of a broader trend toward context-aware AI. “Enterprises have been looking for ways to bring structured data and governance into AI workflows,” said Andrew Brust, CEO of Blue Badge Insights. “Starburst goes further by unifying vector store connectivity for retrieval-augmented generation (RAG) and giving AI agents secure access to governed data products using Trino’s federated architecture—without data movement.”

Key Additions: Multi-Agent Support, Vector Interoperability, and Governance

Starburst’s AI enhancements rest on four core capabilities designed to give organizations flexibility and transparency:

• Multi-Agent Ready Infrastructure: A new MCP (Model Context Protocol) server and agent API enable enterprises to create, manage, and orchestrate multiple AI agents alongside the Starburst agent, supporting collaborative AI-driven workflows.

• Open Vector Store Access: Unified access to vector databases such as Iceberg, PostgreSQL + PGVector, and Elasticsearch allows RAG and search tasks across heterogeneous data environments—without vendor lock-in.

• Model Usage Monitoring & Control: Advanced observability tools let teams track, audit, and limit model interactions through dashboards, improving transparency and cost governance.

• Deeper Insights & Visualization: Starburst’s conversational analytics agent now interprets natural-language queries, identifies relevant data sources, and presents responses as text or visualizations for clearer, faster insights.

These upgrades move Starburst’s lakehouse beyond static analytics dashboards, positioning it as a platform for autonomous, governed decision-making.

Governance at Scale for AI-Driven Enterprises

As AI adoption accelerates, especially in finance, manufacturing, telecom, and public services, enterprises are under pressure to balance innovation with compliance. Starburst’s federated model offers a pragmatic path—letting organizations analyze and operationalize distributed data while maintaining policy enforcement and lineage tracking.

“Companies operating across European borders can confidently build AI and agentic workflows without compromising compliance,” said Matt Fuller, VP of AI/ML Products at Starburst. “Our AI-ready lakehouse is designed with privacy, trust, and performance at its core.”

Starburst embeds metadata-driven policy controls to meet GDPR, Schrems II, and other global regulations, giving enterprises a compliance-first foundation for AI deployment. By avoiding centralized data movement, the platform ensures sovereignty across regions, business units, and multi-cloud environments.

The Road Ahead

As generative AI shifts from copilots to autonomous agents, the infrastructure underpinning these systems must evolve to handle real-time reasoning, transparency, and governance. Starburst’s AI-ready lakehouse signals a clear move toward that future—where AI agents operate responsibly within governed data ecosystems.

The new AI and agentic features will become generally available in Q4 2025.