BOSTON – At its annual AI & Datanova occasion, Starburst immediately introduced the Starburst Enterprise Intelligence Platform, enabling enterprises to run AI straight on ruled information throughout distributed environments.
On the middle of the platform is AIDA, now typically out there, which brings AI-powered intelligence straight into the workflows, functions, and brokers the place enterprise customers work. Starburst additionally launched new AI-Prepared Knowledge Merchandise that present constant enterprise context for queries, fashions, and AI brokers, together with extra capabilities together with Icehouse Ingest and Icehouse LakeOps for Apache Iceberg operations, and Deliver Your Personal Cloud (BYOC) deployments for customer-managed infrastructure.
In keeping with Mavvrik’s 2025 analysis, 84% of corporations report AI prices are decreasing gross margins by greater than 6% — not as a result of AI doesn’t work, however as a result of the info beneath it doesn’t. Knowledge stays fragmented throughout clouds, lakes, SaaS apps, and operational methods, forcing costly information motion, creating governance blind spots, and eroding confidence in AI outputs. The result’s slower, lower-confidence selections, greater prices, and AI initiatives that stall earlier than they scale.
Starburst’s reply is to deliver AI to the info, not the opposite manner round. The Starburst Enterprise Intelligence Platform provides enterprises a single platform to run AI straight on distributed information, in place, with out transferring or replatforming, whereas offering constant enterprise context to queries, fashions, and brokers no matter the place information is saved or processed — throughout clouds, catalogs, and enterprise methods.
Intelligence The place Work Occurs: AIDA
AIDA helps customers transfer from query to motion by producing visualizations, triggering workflows, opening tickets, updating information, and initiating processes throughout linked methods — with out leaving the functions they use. Via help for the Mannequin Context Protocol (MCP), AIDA can even connect with exterior instruments, unstructured content material, and third-party methods to offer richer context throughout enterprise workflows.
“AI has outpaced information structure,” stated Justin Borgman, co-founder and CEO of Starburst. “Most enterprises try to layer AI on prime of fragmented, ungoverned information, and it’s not working. At AI+Datanova, we’re exhibiting a unique path. With the Enterprise Intelligence Platform and AIDA, organizations can lastly operationalize AI – in weeks, not months – on prime of the info they have already got, with out transferring it or rebuilding their stack.”
Constructing the Basis for Trusted Enterprise AI
AI methods produce unreliable solutions after they question information with out understanding what it means. Starburst addresses this via AI-Prepared Knowledge Merchandise, which mix ruled information, metadata, and enterprise definitions into reusable, trusted belongings for analytics and AI, no matter the place information resides.
Relatively than requiring organizations to rebuild semantic definitions from scratch, Starburst previewed its new query-in-place strategy to enterprise context that already exists throughout catalogs, BI instruments, and information pipelines. New AI-Prepared Knowledge Merchandise capabilities embody Knowledge Merchandise as Code, now in public preview, and Automated Metadata Enrichment, now typically out there.
Efficiency & Resilience Constructed for AI-Scale Analytics
Powered by an engine that delivers as much as 2x the efficiency of open supply Trino, Starburst provides enterprises the pace they should run AI and analytics workloads at scale. New resilience capabilities within the Starburst Enterprise Platform (SEP) guarantee mission-critical AI and agentic methods proceed working with out disruption throughout infrastructure failures.
Starburst can also be introducing Managed Icehouse, a brand new functionality constructed on the open structure of Apache Iceberg and Trino — already utilized by Netflix, Apple, Shopify, and Stripe — that automates the complete lifecycle of Apache Iceberg tables throughout two core capabilities:
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Icehouse Ingest for streaming and batch ingestion of recordsdata
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Icehouse LakeOps for clever desk optimization, question tuning and complete desk well being observability
Managed Icehouse provides enterprises a completely managed method to function open lakehouse infrastructure throughout hybrid and multi-cloud environments.
