Qlik & Starburst join forces on enterprise AI data

Qlik has formed a strategic partnership with Starburst focused on enterprise data for business intelligence and artificial intelligence.

The companies will combine Qlik's data integration, replication and analytics tools with Starburst's federated query engine and context layer. The goal is to help customers work across cloud, on-premises and hybrid systems without centralising all of their data.

Large companies often store information across data warehouses, lakes, SaaS applications and internal systems. That can make it harder to apply common governance rules, maintain business definitions and give AI systems reliable access to usable data.

The partnership aims to address that by letting customers query data where it sits and move it only when needed. Qlik will handle workflow orchestration and data logic, while Starburst will serve as the execution engine across distributed environments.

Both companies are also presenting the arrangement as a way to give organisations more flexibility in their data architecture. Instead of requiring a broad migration to a single platform, the model is designed to work with systems already in place across regulated, hybrid and multi-cloud estates.

Joint approach

Under the partnership, the companies are developing integration patterns that combine federated access, shared context and analytics with data integration and transformation. These are intended to support both conventional business intelligence use cases and newer agent-based AI tools.

They have also created validated reference architectures for customers operating hybrid and on-premises environments. These combine Qlik Replicate, Starburst Enterprise and Qlik analytics products for organisations that need to manage data across locations and under tighter regulatory constraints.

Another part of the tie-up focuses on business context. Starburst's context layer and semantic approach are being paired with Qlik's integration and analytics software to help business users and software agents work from governed data and shared definitions.

The companies are also developing AI-assisted data pipelines. In practice, that means tools that can translate natural-language requests into SQL workflows while keeping human validation and control in the process.

Data bottleneck

The announcement reflects a wider issue facing enterprise AI projects. While models and applications have advanced quickly, many companies still struggle with fragmented data estates, inconsistent definitions and governance gaps that can undermine trust in AI outputs.

Centralising all data in one environment can be costly and can raise concerns about latency, compliance and dependence on a single vendor. Leaving data in place without a common layer of governance and meaning can also limit what analytics systems and AI agents can do.

Qlik and Starburst say their combined approach is intended to bridge that gap by linking data access, context and operational workflows. For customers, the message is that they can preserve lineage, policy controls and business meaning while choosing whether to query distributed data directly or move it for specific workloads.

James Fisher, Chief Strategy Officer at Qlik, outlined the company's view of the challenge facing enterprise AI deployments.

"The bottleneck for enterprise AI isn't the models - it's the data architectures they're asked to work with. Fragmented, ungoverned data doesn't just slow AI down; it makes the outcomes untrustworthy," said James Fisher, Chief Strategy Officer at Qlik. "What enterprises need is a way to give AI access to the right data, in the right context, with the right controls - without being forced into a single architecture or a costly re-platforming exercise. That's what this partnership will be built around. Qlik and Starburst give customers the freedom to keep data where it belongs, move it when it creates value, and trust what AI does with it."

Starburst framed the partnership around the need for AI systems to understand the meaning of data, not simply access it.

"Enterprises need more than access to data: they need AI that understands what that data means," said Matt Fuller, Founder and VP of AI & ML at Starburst. "Starburst gives customers governed, federated access to data wherever it lives, with the business context and semantic layer that makes AI answers trustworthy and consistent. Together with Qlik, we give enterprises a practical path from distributed data to trusted business intelligence and AI, without unnecessary data movement, replatforming or vendor lock-in."

Qlik says it is used by 75% of the Fortune 500, while Starburst has built its platform around open standards including Trino and Apache Iceberg.