Qlik Launches Agentic AI, Analytics Capabilities, and a Data Lakehouse at Connect 2025

Qlik, a data integration, data quality, analytics, and artificial intelligence solutions provider, at its Qlik Connect 2025 conference in Orlando, Fla., this week is introducing an agentic AI experience; a series of advancements in Qlik Cloud Analytics; and Qlik Open Lakehouse, a fully managed data architecture built into Qlik Talend Cloud.

The new agentic AI experience will provide a single, conversational interface for users to interact naturally with data, using specialized AI agents to uncover insights.

At the heart of this innovation is the Qlik engine that indexes relationships across data, enabling the discovery of unexpected connections. The agentic experience builds directly on this engine, enabling users and agents to access these relationships, surface insights, and take action across diverse data. It will operate across Qlik Cloud,including data integration, data quality, and analytics solutions.

"This new agentic experience is about removing the distance between data, decisions, and outcomes," said Mike Capone, CEO of Qlik, in a statement. "People want a seamless, conversational way to engage with their data that fits naturally into their work and delivers clear, trusted answers in context. We've built this experience to reflect how decisions actually get made in a business."

Meanwhile, the expanded set of capabilities coming in Qlik Cloud Analytics include tools to detect anomalies, forecast complex trends, prepare data faster, and take immediate action through embedded decision workflows.

Qlik's discovery agent, multivariate time series forecasting, write table, and table recipe work in concert to help companies move from fragmented insight to seamless execution, at scale.

Each capability targets a critical enterprise bottleneck, from delayed awareness to inaccurate forecasting, data prep bottlenecks to disconnected workflows.

• With discovery agent, executives will no longer need to manually track business changes or sift through data. A discovery agent will continuously scan performance across applications and datasets, automatically surfacing critical risks and opportunities before they intensify. Insights are delivered through a personalized feed that clarifies what's happening, why it matters, and suggested next steps.
• The multivariate time series forecasting built into Qlik Predict (formerly AutoML), moves beyond single-variable projections to model the full complexity of business conditions. By analyzing relationships across interdependent variables , like pricing, campaign activity, seasonality, and economic signals , it will deliver sharper forecasts that reflect real-world dynamics.
• Write table will enable users to add context to data records directly in analytics tables, with instant sync across sessions and no reloads required. This capability will enhance in-context data review and lays the groundwork for governed writeback into systems like SAP, Salesforce, and Snowflake — part of Qlik’s long-term vision for integrated, action-ready analytics.
• Table recipe will provide a streamlined, spreadsheet-like experience for preparing single-table datasets. Users will be able to clean, convert, and format data with over 60 visual functions, seeing changes in real time. It will empower non-technical users to prep high-quality data quickly, accelerating the path to reliable insights.

"Enterprises struggle making intelligence accessible and actionable for their business users," said Brendan Grady, executive vice president and general manager of Qlik's Analytics Business Unit, in a statement. "Too many systems deliver insights and answers after the fact. We're building something different: a platform where AI detects what matters, surfaces it in context, and lets you act, all within the analytics environment itself."

Qlik Open Lakehouse delivers real-time ingestion, automated optimization, and multi-engine interoperability. It is powered by Apache Iceberg and maintains full compatibility with the most widely used analytics and machine learning engines.

"Performance and cost should no longer be a tradeoff in modern data architectures," Capone said. "With Qlik Open Lakehouse, enterprises gain real-time scale, full control over their data, and the freedom to choose the tools that work best for them. We built this to meet the demands of AI and analytics at enterprise scale without compromise."