With Starburst AI, built on the company’s foundational data lakehouse system, the company looks to make it easier to “operationalize the agentic workforce” by unifying AI agents with governed data products and metadata.
Starburst continues to expand the functionality of its data lakehouse platform for the AI era, launching new capabilities the company says bring together AI agents with unified enterprise data, governed data products and metadata to better operationalize the agentic workforce.
Built on the core Starburst Data Platform, the new Starburst AI functionality provides a simpler data infrastructure for agentic AI workflows through which agents and people collaborate and so improve agentic productivity, according to the company.
The new offerings build on the company’s mission of “making that very complicated spaghetti of data infrastructure in your business vastly simpler, abstract the complexity, and provide data products that have governance and compliance baked-in [along with] tooling that helps you make that happen faster and accelerate data to the right places,” said Nathan Vega, Starburst senior director of product marketing, in an interview with CRN.
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Starburst “is just continuing on that path to build on top of that infrastructure, to start building the parts and pieces that will allow enterprises to really start adopting agentic workflows and deliver AI productivity to their business,” Vega said.
The need to provide AI systems, including the current wave of agentic AI systems now being developed, with the huge volumes of data they need to function is proving to be a major hurdle for AI adoption and deployment.
“I think one of the things that’s become really obvious, talking with our customers and working with them, is that…AI is a [company] board-level conversation. Every board is speaking about it at every one of their meetings. And what the leaders want is automated decisioning and to boost productivity with AI,” Vega said.
“But the reality is, what’s holding them back is that infrastructure, piece building, establishing a foundation of data access, building around performance and scale, and then enabling curated and consumable insights—that’s holding them back from getting to the place that they need to be with AI,” he said.
Starburst AI is based on the company’s flagship lakehouse platform, with the Trino distributed SQL query engine at its core, that Boston-based Starburst has offered for data analytics tasks since the company’s 2017 launch.
Vega noted that many data management products centralize data within their platforms while Starburst uses a federated data architecture, accessing data wherever it resides.
“Starburst’s federated approach eliminates the need to centralize data while delivering consistent policy enforcement and transparent lineage,” said Matt Fuller, Starburst vice president of AI/ML Products. “The AI-ready lakehouse is designed with privacy, trust and performance at its core, giving teams governed access to the data that matters, whether they’re training LLMs, deploying retrieval-augmented generation, or orchestrating multi-agent workflows, without limitations of legacy architectures or vendor lock-in.”
New Data Capabilities For AI Agents
The latest system developments provide the data governance and compliance functionality of the Starburst system with new, built-in model-to-data architectures, multi-agent interoperability, and an open vector store based on the Apache Iceberg data formatting standard. The new system empowers AI agents with unified enterprise data, governed data products and metadata.
The company also introduced advanced observability and visualization features for its agent framework. The company said that makes it easier to monitor usage of large language model interactions, set guardrails with usage limits, and view activity through intuitive dashboards, improving transparency and governance as AI systems scale.
Starburst AI provides multi-agent-ready infrastructure, open and interoperable vector access, and model usage monitoring and control. Also new is an extension of Starburst’s conversational analytics agent for asking questions across different data product domains and receiving either a natural language response and/or a visualization.
With the latest announcement Starburst is expanding beyond the Starburst AI Agent and AI Workflows product innovations across the company’s Starburst Enterprise Platform and Starburst Galaxy platforms the company announced in May.
“With the Agentic Workforce, enterprises move beyond analyzing data to taking intelligent action,” said Starburst CEO and co-founder Justin Borgman, in a statement announcing the new capabilities. “Our latest innovations bring models directly to governed data, allow AI agents to interoperate across multi-agent ecosystems, and provide open access to vector stores without lock-in. Starburst empowers organizations to scale AI securely and confidently across clouds, borders, and business-critical use cases.”
The latest capabilities are slated for availability during the current quarter.
