Together with Salzburg AG, LexaTexer offers predictive analytics for hydropower plants to support energy producers in decision-making.

LexaTexer X Salzburg AG – Predictive Analytics in hydropower

Together with Salzburg AG, LexaTexer offers predictive analytics, to help corporations in direct decision making, by analysing large amounts of real-world data, including unstructured information, with machine learning technology.

We support utilities and hydroelectric plant operators with operational excellence and bridge the gap between maintenance and market pricing.

Energy production is complex. There is uncertainty associated with energy prices, in addition to uncertainty around the physics of the system like efficiency, erosion rates and optimal maintenance. It is difficult to match current mathematical models, if they are available, with reality. On top, liberalization of energy markets in combination with subsidies in selected niches has introduced a faster and more volatile market environment.

Opportunities & Solution

LexaTexer & Salzburg AG support operators of hydroelectric power plants in optimizing the maintenance time and deriving operating patterns that lead to increased operational efficiency. We use predictive analytics to derive functional dependencies of plant control parameters, gain insights into the workings of turbines and to bridge the gap between operations and market pricing, thus delivering the means to increase operational excellence, react faster to changing market conditions, increase revenue and to optimize maintenance efforts.


Unlike general purpose analytics platforms, we focus on providing industry specific solutions with deep domain-specific knowledge. We provide actionable knowledge rather than uninterpreted information. We recognize and out-of-the-box process more than 570.000 information objects. We have out-of-the-box models to capture the dynamic erosion and other operational parameters. That gives our customers an immediate impact.


Based on our proprietary machine learning platform, we offer solutions to build digital clones of turbines, quantify erosion, calculate optimal maintenance cycles and bridge the gap between pricing and the energy markets.

Markets and Traction

By 2030, over half of the world’s hydropower plants will be due for upgrade and modernization or will have already been renovated. Digitalization provides an opportunity to optimize the design, development and operation of hydropower assets. Our target market includes utility companies and energy trading units.

About us

We offer predictive analytics automation to help companies make direct decisions by integrating and analyzing unstructured, structured and alternative data with machine learning technology.

For more information, contact us via


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