Intelecy no-code industrial AI

Food & Beverage

Transforming the Food and Beverage production with no-code AI

In the competitive food and beverage industry, Intelecy offers an innovative solution to optimize production efficiency, reduce waste, and improve product quality. Our no-code AI platform empowers plant workers to extract meaningful insights from data, enhancing operations seamlessly.

Experience a seamless transformation in your operations with Intelecy and embrace a more efficient future for your production endeavors.

Intelecy enables us to analyse and improve the production, without requiring a Ph.D in programming. This is very exciting for us.
- Kjetil Holstad, Production Manager, Tine
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Food & Beverage use cases

Achieving sustainability with no-code AI

Explore how Intelecy's no-code AI optimizes food and beverage production for sustainability. Learn how our AI predicts optimal processes, maintains asset health, and enhances quality stability, minimizing waste and maximizing efficiency.

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USE CASE

Forecast the future of wastewater
By using Intelecy no-code AI, you can see the future of production processes and, for example, predict when it is the best time to take action.

Learn how process engineers use no-code AI models to predict the future temperature and pH values and thus be able to minimize environmental impact.

 

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USE CASE

Early warning of filter breach
Variations in pressure, flow, or temperature can indicate asset health. But if the variations are minor and the deviations occur over time, it can be impossible for the process engineers to detect.

Explore how the AI models that run live in production see these variations and provide early warnings that prevent waste and reduce downtime.

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USE CASE

Quality related anomaly detection
High quality of end products is crucial. At the same time, process engineers want to prevent unwanted incidents in production that lead to raw materials being lost as waste.

Learn how to gain stable quality by letting no-code machine learning models monitor each subprocess in real-time to detect deviations and prevent waste.

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