Decentralized AI in Metallurgy
Closed-Loop Manufacturing!? Go one step further with our platform and control the manufacturing loop in a data-driven and resource-efficient way without any strategic, legal, or technical headaches.
AI without data in the cloud
The success of AI depends heavily on one component - data.Most customers, however, do not want their data in the cloud.With us, data remains at the plant.Katulu's unique Denzentral Machine Learning approach enables you to use the potential of AI while all sensitive production data stays securely with your customers. Train robust models using Katulu Federated Learning on the rich data and experience your customers bring, for effective digital services such as predictive maintenance or AI-based production optimization.
Higher plant availability
Katulu helps you detect rare failures of system-critical assemblies to avoid plant downtime with predictive maintenance and without any data sharing.
Optimal Energy & Resource Efficiency
Katulu creates the conditions for determining the ideal end time of the melting process using multiple metallurgical plants in the field for optimal energy & resource efficiency.
Harnessing knowledge
Whether it's demographic change or natural workforce turnover, Katulu makes it easier for you and your users to leverage empirical process knowledge.
How can we help?
Do you need a smart solution for a specific use case involving more than one party? Take advantage of our free advice and discuss your case with our AI specialists.
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Free Whitepaper on how Siemens mastered Federated Learning with Katulu
- Learn how Siemens successfully implemented federated learning in two factories combining Katulu’s federated learning platform and Siemens Industrial Edge.
- Deep insights on challenges, experiences, and take-aways from a real-world implementation of federated learning in electronics manufacturing.
- And how Katulu and Siemens enable industrial-grade AI while ensuring privacy, data security, and compliance - plus deep-dive on architecture, technology stack and model performance results.
