
About causara UG
With the help of causara AI technology, classical mathematical optimization models are improved by bringing them closer to the actual conditions and challenges of real-world use cases. This approach is based on machine learning and uses both data-driven surrogate models and large language models (LLMs) to create and efficiently solve approximate optimization models, for example with Gurobi. Additionally, a user-friendly graphical interface (GUI) has been developed that offers AI-powered functions. This makes it possible to flexibly adapt existing models to temporary restrictions or changed framework conditions through simple prompts — even without programming knowledge. Especially for non-technical employees, this opens up the possibility of independently modifying optimization models and adapting them to current requirements. Typical use cases include the optimization of production schedules, route planning, energy deployment strategies, or the dynamic adaptation of supply chains.
