At its annual AI & Datanova conference, Starburst announced the launch of the Starburst Enterprise Intelligence Platform. This new offering allows organizations to run artificial intelligence models directly on governed data across highly distributed environments. The cornerstone of the launch is the general availability of AIDA, an AI Data Assistant designed to embed intelligent capabilities directly into daily workflows, corporate applications, and digital agents. In addition, Starburst unveiled new AI-Ready Data Products to deliver unified business definitions for models, queries, and AI agents, alongside advanced lifecycle operations for Apache Iceberg through Icehouse Ingest and Icehouse LakeOps, and a new Bring Your Own Cloud (BYOC) deployment architecture.
The introduction of the platform addresses a growing financial and structural bottleneck in corporate AI scaling. Research published by Mavvrik highlights that 84% of enterprises experience a reduction in gross margins of more than 6% due to escalating AI infrastructure expenses. This problem doesn’t lie with AI capabilities but with data issues underneath. Business data is still very fragmented across different cloud environments, data lakes, SaaS tools, and transactional systems. The usual solutions make companies go for costly data migration, which also leads to regulatory governance blind spots and lower trustworthiness of AI results. As a result, enterprise decision-making gets delayed, costs of operations increase, and important AI projects don’t get implemented.
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Starburst circumvents this issue by shifting the AI processing layer to the data, eliminating the need to centralize the data stack. The Starburst Enterprise Intelligence Platform provides organizations with a single unified framework to execute AI logic directly on distributed source systems in real time. This query-in-place methodology preserves consistent business definitions and compliance tracking across diverse clouds, data catalogs, and core systems, regardless of where the information physically resides.
“At Vizient, we’re focused on improving how teams across the organization access, connect and use trusted data in a complex healthcare environment. As part of that effort, we’ve been building the foundations for a governed internal data marketplace and reusable data products that support cross-domain analytics and AI enablement. Our approach incorporates a range of technologies, including Starburst, to help teams work more effectively across distributed datasets while reducing unnecessary data duplication,” said Ram Radhakrishnan, Engineering Leader – Data & AI Platforms, Vizient.
“Enterprises are realizing that scaling AI depends less on the models and more on access to trusted, governed data across complex hybrid environments,” said Brad Shimmin, VP & Practice Lead, Data Intelligence, Analytics, and Infrastructure at The Futurum Group. “The industry is shifting toward architectures that reduce data movement while preserving governance and business context. Starburst’s latest announcement reflects that trend with a focus on distributed data access, embedded AI, and enterprise-scale analytics performance.”
AIDA: Embedding Intelligence directly into Corporate Workflows
With AIDA moving to general availability, corporate executives and business units can access actionable insights without waiting on centralized data teams or static reporting dashboards. Running natively within existing application landscapes, AIDA interfaces across distributed data repositories in real time. The technology utilizes Starburst’s AI-Ready Data Products to enforce uniform business definitions and governance compliance during runtime queries.
AIDA converts standard natural language queries into automated operations, giving users the power to build data visualizations, trigger enterprise workflows, log operational tickets, update internal records, and launch cross-system processes from within their primary applications. By supporting the Model Context Protocol (MCP), AIDA seamlessly connects to external developer tools, unstructured document repositories, and third-party software platforms to enrich corporate context.
“AI has outpaced data architecture,” said Justin Borgman, co-founder and CEO of Starburst. “Most enterprises are trying to layer AI on top of fragmented, ungoverned data, and it’s not working. At AI & Datanova, we’re showing a different path. With the Starburst Enterprise Intelligence Platform and AIDA, organizations can finally operationalize AI in weeks, not months on top of the data they already have, without moving it or rebuilding their stack.”
The Structural Core for Trustworthy Enterprise AI
To prevent AI systems from generating flawed or hallucinated responses due to a lack of data comprehension, Starburst has introduced its AI-Ready Data Products. These assets encapsulate secure data, rich metadata, and standard business logic into reusable packages optimized for analytical engines and AI applications.
Rather than requiring engineering teams to construct new semantic models from scratch, Starburst previewed an in-place querying method that reads pre-existing business logic across current catalogs, BI dashboards, and pipeline configurations. Key features driving this data asset framework include Data Products as Code (now in public preview) and Automated Metadata Enrichment (now generally available).
Analytics Performance Optimized for AI Scale
Operating on a proprietary engine optimized to deliver up to double the performance speed of open-source Trino, the Starburst platform provides the processing velocity required to execute large-scale AI and analytical computations. Enhanced resilience protocols embedded in the Starburst Enterprise Platform (SEP) ensure that mission-critical AI services and agent networks remain active without disruption during hardware or infrastructure drops.
Additionally, the company launched Managed Icehouse, a fully automated solution tailored for open lakehouse management using Apache Iceberg and Trino technologies trusted by digital leaders like Apple, Netflix, Shopify, and Stripe.
The solution automates table lifecycles through two main avenues:
- Icehouse Ingest: Handles real-time streaming and high-volume batch file ingestion.
- Icehouse LakeOps: Provides intelligent table optimizations, automated query tuning, and complete structural observability.
Managed Icehouse provides enterprises with a turn-key strategy to operate open lakehouse environments across hybrid and multi-cloud systems.
Managed Analytics Inside Customer Cloud Environments
A recently released BYOC Deployment option for use in preview mode will enable the incorporation of all Starburst Galaxy services in the customers’ particular cloud environments. This approach provides full control by enterprise IT departments over networking options, storage solutions, security boundaries, and compliance procedures. The compute workload along with the network infrastructure and enterprise-level data stay in the cloud accounts of respective clients.
