RISC Software GmbH develops data-driven algorithms and simulation methods tailored to the needs of the industry. Our solutions enable real-time analysis of complex production processes, optimize workflows, and increase resource efficiency. We rely on machine learning, advanced algorithms, and big data analytics to support precise, data-driven decision-making. The focus is on manufacturing processes, material flows, real-time simulation, and production line optimization.
A central component of our work is the development of digital twins – virtual replicas of real systems. These allow the simulation of processes, early detection of potential issues, and proactive testing of solutions. This enables risk minimization, improved planning, and maximized efficiency.
With digital twins, companies can:
The close connection between scientific research and industrial practice is our recipe for success. Through interdisciplinary teams and state-of-the-art simulation tools, we develop customized solutions that are already successfully used in light metal production, traffic data simulation, and material flow optimization.
Discover how Industrial AI and simulation can transform your processes. Contact us – we will show you the potential within your company.
In the FusionTool-AI research project, RISC Software GmbH and its partners are developing an AI-based tool that decides whether forming tools should remain in operation, be regenerated or be replaced.
Together with Industrie Informatik GmbH, RISC Software GmbH developed a comprehensive planning solution for production planning.
InProSSA combines symbolic & sub-symbolic AI in one language to solve problems model-independently & choose the optimal approach automatically.
The Secure Prescriptive Analytics project aims to develop an innovative modeling concept that breaks down complex systems, such as industrial plants, into variable sub-models and represents them using proxy models. The aim is to create an open source platform that supports the optimization and linking of these models.
The aim of the project is to enable the use of methods from prescriptive analytics / machine learning in our automation projects. The core objective is the in-line optimization of the parameters on which the control algorithms are based.
RISC Software GmbH supported the LKR Leichtmetallkompetenzzentrum Ranshofen in rolling out a software product for production in continuous aluminum casting. This software enables precise parameter configuration via a web application. The Docker platform was used to combine different user environments and versions.
RISC Software GmbH supports its customers with long-standing practical experience in the development of customized AI-driven solutions for extracting value from unstructured (text) data.
Maximize the potential of your data and pave the way for the successful application of artificial intelligence with a professional AI data check.
Automated data analysis, validation, and training machine learning models
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