Deliver No-code, Automated Machine Learning to Analytics Teams

Create ML experiments, identify key drivers in your data, and train models — all to see what might happen, and why.

Illustration of a data analytics software interface showing model metrics, feature importance, and key driver identification for various classification models.

Give analysts the power of predictive analytics

Generate models easily

Identify key drivers in your data and generate models with unlimited experimentation.

Make predictions

Reports include full explainability so you can understand what might happen and why.

Test scenarios

Experiment without the risk of failure or the need for excessive effort — like coding.

Publish your experiments

Publish data quickly to Qlik Cloud® Analytics for interactive exploration, real-time models, and what-if analyses.

How no-code machine learning works

Click to watch the Qlik AutoML demonstration video.

Auto-generate machine learning models

Identify key drivers in your historical data and use the best algorithms to generate machine learning models. Simply select a target field in your data set and let Qlik AutoML do the work:

  • Determine key drivers in your historical data

  • Auto-generate predictive models with unlimited tuning and refinement

  • Select and deploy the best-performing models based on scoring and ranking

A flowchart illustrating the steps of a machine learning process: ML-ready dataset, feature selection, model generation, model tuning and iteration, model deployment, predictions, scenario exploration, and informed actions.

Predict potential outcomes

Just load data to automatically generate likely outcomes based on your predictive model. And more importantly, get explainability data (SHAP values) at the record level, so you know why predictions were made and how to best influence outcomes.

A software interface displaying SHAP importance scores, customer churn prediction influencers, current data, deployed model, and a selected territory marked as CT.

Explore predictive data and test what-if scenarios

Qlik's Associative Engine provides real-time, instant calculations to explore. Make interactive selections and shift parameters in what-if scenarios, then evaluate the results to get a feel for what actions will lead to the best outcome.

Illustration of a Qlik dashboard titled 'Customer Churn - What-if Analysis' showing 'Prediction Influencers' and a 'What-if' customer churn metric with a value of 35.98% and selectable plan types.


AI Trends for 2024

Follow the path to trusted data. Explore the top AI trends for 2024 and learn how to turn your big data into better data.

AI Trends for 2024 Background Image
A magnifying glass focuses on a digital chart with bars and lines, symbolizing data analysis and examination. Surrounding elements include abstract shapes in shades of green and blue.

Here are some important AutoML use cases







Supply Chain

Service and Support

AI and Machine Learning Connectors

Easily connect with top AI and machine learning tools like Open AI, Amazon Bedrock, Azure ML, or Databricks ML.

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By building AI into everything they deliver, while still maintaining a cloud agnostic approach, Qlik is meeting customers where they are in their AI journey while providing the flexibility needed to expand AI where and how it makes sense.

Dan Vesset
Group Vice President, Analytics and Information Management Market Research & Advisory Practice, IDC
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