en.Wedoany.com Reported - Starburst announced the launch of its Enterprise Intelligence Platform at the AI & Datanova conference, enabling enterprises to run AI directly on governed data within distributed environments. The platform's core component, AIDA, has been officially released, integrating AI-driven intelligence into business users' workflows, applications, and agents. Simultaneously, Starburst introduced AI-Ready Data Products, which provide consistent business context for queries, models, and AI agents, along with additional features such as Icehouse Ingest, Icehouse LakeOps for Apache Iceberg operations, and BYOC (Bring Your Own Cloud) deployment for customer-managed infrastructure.
Research by Mavvrik in 2025 shows that 84% of enterprises report AI costs causing a decline in gross margins exceeding 6%, not because AI itself is ineffective, but because the underlying data fails to deliver value. Data remains scattered across clouds, data lakes, SaaS applications, and operational systems, leading to high data migration costs, governance blind spots, and diminished confidence in AI outputs, ultimately resulting in slower decisions, reduced trust, rising costs, and AI projects stalling before they can scale.
Starburst's approach is to bring AI to where the data resides, rather than moving the data. Its Enterprise Intelligence Platform provides a unified platform for enterprises to run AI directly on distributed data in place, without the need for movement or re-platforming, while delivering consistent business context for queries, models, and agents, regardless of where the data is stored.
Ram Radhakrishnan, Head of Data & AI Platform Engineering at Vizient, stated that the team is focused on improving how teams access, connect, and use trusted data within healthcare environments. They are laying the foundation for governed internal data marketplaces and reusable data products through a suite of technologies, including Starburst, to reduce unnecessary data duplication. Brad Shimmin, Vice President and Practice Lead for Data Intelligence, Analytics & Infrastructure at The Futurum Group, noted that the bottleneck for scaling enterprise AI lies in the ability to access trusted, governed data across complex hybrid environments. The industry is shifting towards architectures that minimize data movement while preserving governance and business context, a trend reflected in Starburst's latest release.
Starburst's AIDA is now generally available, designed for executives and business users who cannot wait for dashboards or data teams, enabling them to run AI directly within the workflows, applications, and agents they use. AIDA does not rely on centralized or duplicated data; instead, it operates in place on distributed enterprise data, leveraging AI-Ready Data Products to provide consistent business definitions and governed context at runtime. AIDA helps users move from questions to action, generating visualizations, triggering workflows, submitting tickets, updating records, and initiating processes across connected systems—all without leaving the current application. It also supports the Model Context Protocol (MCP), allowing connections to external tools, unstructured content, and third-party systems.
Justin Borgman, Co-founder and CEO of Starburst, stated that AI has outgrown data architectures, and most enterprises are trying to layer AI on top of fragmented, ungoverned data, but this approach does not work. With the Starburst Enterprise Intelligence Platform and AIDA, enterprises can operationalize AI within weeks, building on existing data without needing to move or rebuild their technology stack.
To ensure the reliability of AI outputs, Starburst combines governed data, metadata, and business definitions into reusable, trusted assets through AI-Ready Data Products. New features include Data Products as Code (now in public preview) and Automatic Metadata Enrichment (now generally available). Furthermore, powered by an engine with performance up to twice that of open-source Trino, the Starburst Enterprise Platform (SEP) has enhanced resilience capabilities, ensuring mission-critical AI and agent systems continue operating during infrastructure failures. Starburst also launched Managed Icehouse, a new feature built on the open architecture of Apache Iceberg and Trino (used by Netflix, Apple, Shopify, and Stripe), which automates the full lifecycle of Apache Iceberg tables. It includes Icehouse Ingest for file, streaming, and batch ingestion, as well as Icehouse LakeOps for intelligent table optimization, query tuning, and comprehensive table health observability.
Starburst introduced the BYOC deployment model (now in preview), extending Starburst Galaxy into customer cloud environments. Customers retain compute, network, and data within their own cloud accounts while benefiting from Starburst's managed experience, eliminating the trade-off between operational simplicity and infrastructure sovereignty.
Currently, AIDA is generally available on both Starburst Galaxy and the Starburst Enterprise Platform. Starburst managed capabilities for BYOC deployments are in preview, with a design partner program underway. New Starburst Enterprise Platform enhancements are available in private and public previews, with some features included in the May 2026 LTS release.
Starburst is dedicated to delivering enterprise intelligence at scale by providing organizations with secure, governed access to all their data. Built specifically for distributed data environments across on-premises systems, multi-cloud, and hybrid architectures, the company helps enterprises power AI and analytics. Starburst is built on open standards such as Trino and Apache Iceberg, aiming to help organizations avoid vendor lock-in.
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