AGENTIC DATA ENGINEERING
Declarative Data Pipelines, defined in code
Define Qlik Talend Cloud® pipelines as YAML-based code that AI coding agents such as Claude Code or GitHub Copilot can read, generate, and update.
BUILD YOUR WAY
Meet data engineers where they work
Build pipelines visually, manually, programmatically, or agentically.
Prompt your coding agent
Prompt your coding agent from your Integrated Development Environment (IDE). It pulls the pipeline context it needs from your GitHub repository, then generates or modifies the pipeline for you to commit and deploy.
NEW MCP TOOLS
Bring pipeline context into your coding workflow
Describe the outcome and let your agent do the work
Declarative data pipelines keep every change readable, comparable in a diff, and reusable across environments.
Edit locally with AI help
Edit the project YAML files in your IDE. For complex configurations, a supported AI assistant configured with the project instructions file can help generate and refine YAML.
Catch errors before you commit
Schema validation highlights errors in real time as you edit, and a validation API can check a project before import.
Promote across environments
Apply your changes to Qlik Cloud®, then promote the same pipeline definition across development, verification, and production with environment-specific binding values.
Trusted data, not just faster pipelines
Team up with a Gartner® Magic Quadrant™ Leader
in three categories
Reuse definitions and automate at scale
Reuse pipeline definitions as templates across projects or teams to keep work consistent and reduce duplication. Create and update projects programmatically, without manual work in the Qlik Cloud user interface.
