The simulation landscape is undergoing a fundamental transformation. With increasing complexity in design tasks, rising energy costs, and the demand for shorter development cycles, companies are looking for solutions that are not only faster but also smarter. In this context, AI-driven agents offer a new paradigm: they combine intelligent automation, high-performance computing (HPC), and cloud-native simulation services to optimize development processes in real-time. In our recent webinar, we explored how AI agents are changing the way simulation and optimization are executed, and how they can help companies sustainably improve efficiency, reduce unit costs, and minimize energy consumption.

At the core of this transformation lies the integration of AI agents into cloud-based simulation ecosystems. These agents act autonomously and interact iteratively with digital models and services, orchestrating simulation workflows, generating new design variations, and evaluating performance metrics — all without human intervention. The key advantage: AI agents work continuously in closed-loop optimization cycles and can intelligently prioritize promising designs while discarding inefficient configurations early on. This not only saves computational resources but also leads to faster convergence towards optimal solutions.

A critical component of this approach is the use of surrogate models. Unlike high-fidelity simulation models, which are computationally intensive and often require supercomputers to run, surrogate models are trained on synthetic data and provide fast, approximate predictions of simulation results. This enables agents to evaluate large design spaces efficiently, while still maintaining sufficient accuracy for meaningful optimization. Combined with high-resolution CFD simulations and parametric digital twins, AI agents are capable of exploring and improving complex geometries such as extrusion dies, injection molding parts, and blow mold tools.

Another advantage of this AI-driven approach is the cloud-native infrastructure. All simulation and optimization processes are executed on secure HPC clusters located in Germany, ensuring maximum performance, scalability, and data protection. Engineers and decision-makers can access simulation results from any device, collaborate in real time, and interact with AI systems through intuitive cloud dashboards. This enables cross-functional teams to make faster, more informed decisions — regardless of their location or simulation expertise.

From a technical perspective, the AI agents utilize for instance Bayesian optimization algorithms to traverse the design space in a probabilistic manner. This allows them to balance competing design goals, such as minimizing residence time and velocity variance in extrusion processes, or reducing deformation in injection-molded components. The agents rely on robust, scalable services that automatically generate meshes, run simulations, and analyze results — even when dealing with highly sensitive, multi-parameter designs. The result: reduced simulation times, lower energy consumption, and more accurate outcomes.

Beyond performance, cost control is a central objective of AI-driven simulation. Poorly configured simulation workflows can quickly lead to unnecessary expenses — particularly in large-scale optimization campaigns involving thousands of design variations. With intelligent scheduling, cloud monitoring, and failure handling, AI agents help avoid common pitfalls and ensure that only valuable computations are executed. This significantly improves the cost-efficiency of simulation-driven development projects.

In practical terms, AI agents enable companies to not only automate repetitive tasks but also scale their simulation efforts without increasing headcount or infrastructure. Whether optimizing window frame extrusions, improving injection molding layouts, or balancing multi-material flows, AI agents provide a strategic edge for innovation-driven teams. The result is a more agile, resilient, and energy-conscious product development process.

Let’s bring intelligence into your simulation workflows

AI agents represent the next generation of simulation technology — fast, autonomous, and optimized for sustainability. At IANUS, we combine advanced CFD models, AI-based optimization, and a secure cloud platform to deliver scalable simulation solutions tailored to your needs. Curious how intelligent agents can support your engineering challenges? Book a consultation with our team today and explore the future of simulation with us.