Qlik, a world-renowned company in data integration, analytics and artificial intelligence, has released an upgraded version of its agentic execution strategy. The company has added new intent-driven features to its data engineering suite which will enable the data teams to design, develop and deliver AI-ready data products at the pace aligned with the business addressing the main problem in modern enterprise automation.
As AI schemes progressively turn from experimental models to production-grade agents, the challenge faced by the data teams has become unbearable. Prior to this, the organizations were limited by their AI desire, but now the limitation is the manual work to build pipelines, troubleshoot transformations and make data fresh enough for autonomous decision-making. Qlik’s new version changes the concept from manual coding to higher-level orchestration, and this will allow the engineers to convert natural language intent into solid, production-ready data assets.
“Most companies do not struggle to imagine AI use cases. They struggle to deliver the trusted, current data those use cases depend on,” said Mike Capone, CEO, Qlik. “As demand rises, data engineering becomes the critical path. Qlik is helping teams reduce friction, protect trust, and keep pace with the business.”
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A New Architectural Foundation for Agentic Workflows
Qlik’s expanded portfolio introduces several “agent-first” capabilities designed to automate the data engineering lifecycle:
Declarative Pipelines: The engineers can now create data pipelines using an interface driven by natural language. With the help of a pipeline canvas and suggestions on the next step, a team can reduce the technical hurdle to building a sophisticated integration while having complete control over their architecture.
Contextual AI Assistant for Talend Studio: This contextual assistant within the Talend Studio IDE, slated to be released in the coming months, assists developers in creating jobs, writing SQL and documentation using natural language commands.
Real-Time Routing for Agentic Data Flows: Qlik is extending Talend Studio to support real-time message routing for agent-based processes. This allows engineers to build domain-specific Retrieval-Augmented Generation (RAG) pipelines and connect complex agentic systems through Model Context Protocol (MCP) components.
Open Lakehouse Streaming: Native streaming support is now integrated into Qlik’s Open Lakehouse. This allows teams to unify continuous event data with traditional batch and Change Data Capture (CDC) workloads in a single environment, ensuring AI models operate on the most current business conditions.
From Manual Toil to Intent-Driven Engineering
By combining declarative pipelines with real-time streaming and AI-assisted development, Qlik is positioning data engineering as a more strategic, intent-driven function. This “Pipeline Agent” approach allows engineering teams to focus on design and business impact rather than basic pipeline assembly.
“There is a big difference between an assistant that helps write code and a system that actually helps a data team move faster end to end,” said Robin Astle, Principal Developer, Valpak. “The interesting part of this announcement is the focus on pipeline creation, data quality, metadata, and stewardship together, because that is much closer to how real engineering work happens.”
The new capabilities are available immediately as part of the Qlik Talend Cloud, providing a scalable, agent-assisted operating model that ensures data reliability is never the weak link in an enterprise’s AI strategy.