INTELECY NO-CODE INDUSTRIAL AI

Power & Renewable Energy

Transforming energy efficiency with no-code AI

In a world facing increasing demand and environmental challenges, green energy solutions are becoming imperative. To navigate these challenges, precision is crucial. Utilizing AI, big data, and no-code technology, operators can now make accurate forecasts, enhance flexibility, and optimize maintenance processes.

No longer confined to specialists, no-code AI empowers plant workers, ensuring quick value realization. Discover how power companies are leveraging this revolution to optimize processes, reduce emissions, enhance safety, and balance power-demand dynamics.

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With the right user-friendly tools, maintenance and reliability engineers can use their competence of the assets to build machine learning models to monitor and understand equipment behavior. The insight puts them in a better position to eliminate unnecessary maintenance and prevent breakdowns. This is the future of maintenance management.
- Thomas Brunjulfsen, Head of Digitalization, Maintech
Maintech
Power & Renewable Energy use cases

Empowering sustainable energy solutions

Discover how Intelecy's no-code AI models empower sustainable energy solutions in the power and renewable energy sector. Explore actionable insights for emission reduction, predictive maintenance, and energy demand forecasting, driving efficiency and environmental responsibility.

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USE CASE

Actionable insights to reduce emissions
Learn how no-code AI models can provide actionable insights for emission reduction by predicting the future value of harmful gases and providing early warnings of deviations in the cleaning process. 



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USE CASE

Early warning and predictive maintenance on critical assets
Seasonal variations in weather and temperature are difficult to predict and can cause major fluctuations and challenges related to asset health. Learn how multivariable no-code AI models are used for predictive maintenance to prevent costly and, in worst case, critical asset downtime.

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USE CASE

Forecast energy demand
By producing in an optimal balance between supply and demand, the energy plant will improve raw material utilization and increase production and distribution cost efficiency.
 
Discover how forecast no-code machine learning models predict the future energy demand.

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