cimt

Qlik Product · Predict

Qlik Predict — predictive AI without a data science team

Build, train and deploy forecasting models directly from Qlik Cloud — without Python, R or a dedicated data science team. Predictions appear directly as calculations in your existing Qlik Sense apps.

Qlik Predict (formerly Qlik AutoML) is the no-code predictive analytics solution within Qlik Cloud. It enables business analysts and data analysts to build, train and deploy forecasting models — without Python, R or a dedicated data science team. Fully integrated in the Qlik Cloud platform: it works on the same data already available in your Qlik Sense environment, and predictions become directly usable in dashboards and decision making. Four core capabilities: automated feature engineering, no-code model building, model monitoring with drift detection, and embedded predictions. For business use cases like demand forecasting, churn prediction, anomaly detection and revenue forecasting, Qlik Predict delivers 80% of the value of a custom ML stack at a fraction of the complexity.

Core capabilities

What Qlik Predict does for you

No-code model building

Select a dataset, choose a target variable and let Qlik Predict automatically build and validate the best model.

Automated feature engineering

The platform automatically identifies the most predictive variables and transformations — no manual preprocessing.

Model monitoring

Continuous monitoring of model performance with automatic alerts on model drift due to changing data patterns.

Embedded predictions

Predictions become directly available as calculations in Qlik Sense apps — no separate interface needed.

Use cases

Applications that deliver direct results

cimt helps identify the right use cases, prepare data and implement — from proof of concept to production. Often usable models within 6–10 weeks.

Use case Description Sector
Demand forecasting Forecast demand for products or services based on historical patterns, seasonality and external factors Retail, Manufacturing, Logistics
Churn prediction Identify customers with elevated risk of leaving and take proactive action Telecom, SaaS, Insurance
Anomaly detection Detect deviating patterns in processes, transactions or sensor data Finance, IoT, Healthcare
Revenue forecasting Forecast revenue by product line, region or channel for budgeting and planning All sectors

Quick quote

Request a quote for Qlik Predict

Qlik Predict is an add-on for Qlik Cloud Enterprise. Fill in the form and we'll work out which edition + capacity fits your situation, including a first use case workshop.

We respond within one business day. Quote goes to sales@cimt.nl.

Frequently asked

Qlik Predict in practice

Do I need data science knowledge to use Qlik Predict?

No. Qlik Predict is designed for business analysts and data analysts without programming experience. The platform automates the full modelling process: feature selection, training, validation and deployment. But your data needs to be well prepared and of sufficient quality — cimt helps via our Data Governance and Data Quality services.

Is Qlik Predict part of my Qlik Cloud licence?

Qlik Predict is available as an add-on for Qlik Cloud Enterprise. Availability and pricing depend on your current edition and capacity. Contact us for tailored licence advice — as Elite Partner we have direct access to Qlik volume discounts.

How reliable are the predictions?

Qlik Predict provides extensive model validation with metrics like RMSE, MAE and R-squared for regression and AUC, precision, recall for classification. The platform also shows feature importance so you understand which variables drive the prediction. Model monitoring automatically flags when performance degrades due to changing data patterns — no 'silent degradation'.

For which problems is Qlik Predict not the right choice?

For complex domain-specific models (computer vision, NLP, custom deep learning, reinforcement learning) a data science team is still needed. Qlik Predict fills the 80% where business analysts get the most value: tabular data, standardised algorithms (regression, classification, time series). For exotic use cases we often recommend a combination: Qlik Predict for the broad part, custom ML for special models.