Starburst unveils AI Agent & Workflows for enterprise data

Starburst has launched new AI Agent and AI Workflows products to support enterprise customers in building and deploying artificial intelligence applications more efficiently while meeting requirements for security, compliance, and control.

The newly announced features will be integrated within Starburst's enterprise-grade data platform, providing access to data distributed across cloud, on-premises, or hybrid infrastructure options. According to the company, this approach aims to accelerate enterprise adoption of AI technologies, control operational costs, and help organisations realise value from data initiatives at a faster pace.

Starburst's product portfolio enhancements span its flagship offerings: Starburst Enterprise Platform and Starburst Galaxy. The additions of Starburst AI Agent and Starburst AI Workflows are intended to support the adoption of modern data architectures designed for AI, analytics, and associated application development by providing centralised, governed, and efficient access to distributed and hybrid data.

AI Workflows is positioned as a suite of capabilities that brings together vector-native search, metadata-driven context, and governance in an open data lakehouse environment. This suite aims to enable enterprises to move AI projects through experimentation to production stages with improved speed and control.

The Starburst AI Agent introduces an out-of-the-box, natural language interface for Starburst's data platform, allowing both data analysts and AI agents at the application layer to derive insights with greater ease for business stakeholders. The integration of AI Workflows and AI Agent is expected to provide faster performance, lower overall costs, and higher levels of data governance, security, and compliance.

Justin Borgman, Chief Executive Officer and Co-Founder of Starburst, commented, "AI is raising the bar for enterprise data platforms, but most architectures aren't ready. At the end of the day, your AI is only as powerful as the data it can access. Starburst is removing the friction between data and AI by bringing distributed, hybrid data lakeside, enabling enterprise data teams to rapidly build AI, apps, agents, and analytics on a single, governed foundation."

Matt Fuller, Vice President of AI/ML Products at Starburst, outlined the flexibility of the new offerings. He said, "We're turning the data lakehouse into an enterprise-grade platform for AI agents and applications - designed from the ground up to support air-gapped environments without compromising on flexibility. Whether deployed in a secure on-premise environment or cloud-enabled ecosystem, Starburst delivers federated, governed access, real-time context, and high performance query processing. We're not just accelerating AI innovation; we're operationalizing it, securely and at scale."

Rob Strechay, Managing Director and Principal Analyst at theCUBE Research, remarked on the value proposition of Starburst, saying, "Starburst uniquely helps enterprises speed up AI adoption, reduce costs, and realize value faster by enabling access to all their data, no matter where it lives, across clouds, on-premises, or hybrid environments. The best part? Because data has gravity, they don't need to move or migrate it to build, train, or tune their AI models."

Starburst's customers have reported benefits associated with these new capabilities. George Karapalidis, Director of Data at Checkatrade, said, "User Role-Based Routing in Galaxy made it simple to direct queries to the right cluster based on team roles. It's intuitive, seamlessly integrated into the Galaxy UX, and helps us optimize for both performance and cost without adding operational overhead."

Ricardo Cardante, Staff Engineer at Talkdesk, described operational efficiencies achieved with Starburst: "Before Starburst, maintaining our Iceberg tables was a manual, error-prone process that only covered a fraction of our data. With Automated Table Maintenance, we applied compaction and cleanup across the board, going from 16% table maintenance coverage to 100%. This enhancement led to a 66% reduction in S3 storage costs for our data platform buckets and contributed to an overall 20% decrease in S3 storage expenses across the company. It's a game changer for scaling Iceberg performance with minimal overhead."

The update also includes enhancements such as AI-Powered Auto-Tagging for data governance, a new Data Catalog for metadata management, fully managed Iceberg pipelines, improved query performance with a Starburst-native ODBC driver, and automatic query routing in Starburst Galaxy. Customers can further benefit from features such as live table maintenance, streaming and batch ingest options, as well as strengthened governance for secure, self-service data access across teams.

The AI Agent and AI Workflows are available for pilot use in private preview, and additional capabilities—including metadata management, table management improvements, and automatic query routing - are arriving in phases, with selected features already generally available or expected to enter public preview soon.