Qlik has expanded its work with Snowflake to bring more enterprise data and governed context into Snowflake workflows. The move includes a native application linking Snowflake Intelligence and Cortex Agents with Qlik Cloud.
The update focuses on three areas: moving data from enterprise systems into Snowflake in real time, adding governance and business context to analytics and AI workflows, and tying those workflows to operational action. It is aimed at organisations trying to move beyond limited artificial intelligence projects into broader use across business processes.
At the centre of the announcement is a Snowflake Native App for Qlik Model Context Protocol Server. It is designed to let Cortex Agents access Qlik-governed data and analytics assets from within Snowflake workflows, including Qlik apps, key performance indicators, formulas, chart data and lineage information.
That gives Snowflake users a way to bring Qlik-governed information into natural-language exploration and AI-led workflows without limiting the context to data already stored in Snowflake. Relevant business context may also come from systems outside the data platform.
Data flows
Qlik can move data into Snowflake from SAP systems, mainframes, software-as-a-service applications, databases and streaming environments. It supports change data capture, streaming, batch and event-driven data movement from what it described as hundreds of enterprise sources.
The emphasis on real-time and near-real-time access reflects a broader challenge in corporate AI efforts. For many businesses, the main obstacle is not access to models but getting current data into the right place, preserving its meaning, and setting rules for how outputs are used in live workflows.
Qlik is positioning its products around that problem by combining data integration, data quality, analytics and open agent interoperability. It said this can help customers create governed data products that include lineage, quality controls, stewardship and trust signals.
Partner focus
The announcement also highlights the importance of partnerships around large data platforms as suppliers try to secure a place in the AI software stack. Snowflake has sought to present its platform as a base for enterprise AI work, while partners such as Qlik are trying to show how external tools can add data sources, governance and business logic.
For joint customers, that means extending Snowflake with analytics and governed context rather than replacing existing investments. Qlik said its products are designed to fit with the systems customers already use, including operational systems, documents and streaming data environments.
Josh Good, Vice President, Tech Ecosystems & Strategy at Qlik, said the issue for customers is practical delivery rather than experimentation. "Snowflake customers do not need more AI experimentation around the edges," Good said. "They need a practical way to get more value from Snowflake by bringing in more enterprise data, preserving business context, and connecting Snowflake and Cortex workflows to governed intelligence across the business. Qlik helps do that with the flexibility and control enterprises expect."
Snowflake described the development as a way to expand the amount of governed data available inside its environment. "Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data," said Amy Kodl, Senior Vice President, Worldwide Alliances and Channels at Snowflake. "Qlik complements that foundation by helping joint customers connect more enterprise data and business context to Snowflake workflows, so teams can move faster from data to insight to action with the governance required at enterprise scale."
Governance layer
Governance is a central part of the message. Qlik said customers can create curated, reusable data products with controls over quality and lineage, intended to improve confidence in analytics and AI-driven decisions. That is likely to resonate with large companies that need to track where data comes from and how it is used, particularly in regulated processes or sensitive operational decisions.
Qlik also highlighted open agent interoperability, reflecting industry efforts to avoid creating isolated AI systems that cannot work across different tools and platforms. By linking Snowflake Intelligence and Cortex Agents to Qlik Cloud through the native app, it is trying to place its analytics layer inside broader agentic workflows rather than treat analytics as a separate endpoint.
The approach is particularly relevant in environments where SAP data, operational systems, documents and real-time streams all need to work together under governance.