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Castalytics GmbH is focused on applied artificial intelligence for different industries.
With the Castalyze method, internal and external data are meshed, valuable patterns and relations are identified using precise self-learning algorithms.
This enables companies to gain insights on company management, open up untapped business potential and shape their business in the future.
Castalytics is build on the experience of enercast in Power Forecast / Analytics and Big Data Management.
By the application of artificial intelligence, Castalytics increases the added value of systems and products by up to 25%.
Artificial intelligence as a productivity factor
More than digital optimization – AI opens up new growth potentials
Digitalization is only the first step
Analog Business Model
Low degree of automation and digitization
Digital business model
Mapping of analog processes to digital processes
Automation of subprocesses
Fully digital business model
Complete digitalization of all main processes
Applied AI as a productivity factor
Self-learning algorithms for permanent optimization
Castalytics at a glance
Technology company for applied artificial intelligence
Your Data – Your Success:
AI-based big-data analysis in the company’s data base
Correlation of internal and external data (e.g., weather data)
Precise identification of value drivers and previously undiscovered
patterns with the Castalyze™ method and implementation in control
Permanent optimization by self-learning algorithms
Measurable results within a very short time:
Efficient new control parameters
High-precision forecasts (e.g., 97.5% accuracy in day-ahead RES feed-in forecasts)
Significant increase in value added
Proven success in various industries
AI provides answers to millions of questions. The CASTALYZE™ method provides answers to the key question of how to increase the value of your business.
IDENTIFY – SIMPLIFY – AMPLIFY
Identification of data clusters in the company
Internal Data connections
Optional: connect external data (e.g., weather data)
Big-data analysis using artificial intelligence
Recognition of patterns and correlations
Identification of the value drivers
Elimination of ”corrupt data“
Development of related control signals
Translation of the analysis findings into process-relevant control signals
On the basis of concrete customer requirements (optimization)
On the basis of newly discovered value drivers / with abolition of the process restrictions (new productivity factor)
Process simulation with different AI algorithms
For verifying the control signal
To determine the economic potential
Meta-AI identifies best algorithm (highest signal quality + highest economic lever)
Implementation in the production process
Identification of the respective best feed-in point for the control signals
Implementation in the operational production processes
Fully automated in machine-to-machine processes (digital control in real-time)
Part-automated with decision-making support for employees (faster response, better decisions)
Analysis of the production data / re-analysis
Continuous optimization and re-evaluation of control signals and processes using self-learning algorithms