HORSHAM, PA — Aegis Software has added built-in Model Context Protocol support to its Simio simulation and planning software, allowing manufacturers and other operators to connect compatible generative AI applications and use natural-language commands to analyze models, troubleshoot problems and evaluate production plans.
The standards-based capability allows organizations to use their preferred compatible generative AI applications, including those powered by large language models, rather than relying on a single AI interface.
Users can generate or refine model logic, examine how an existing simulation works, diagnose errors and run or analyze experiments. In planning and scheduling applications, teams can investigate production results, including late orders and characteristics those orders have in common.
The integration is designed to reduce the expertise and time required to work with complex simulation models while accelerating routine tasks for experienced users.
“What the new built-in MCP support changes is how teams can work with Simio,” Aegis Chief Executive Officer Jason Spera said. “AI-powered interaction can enable more people to contribute, help experienced users work faster and allow organizations to gain value from simulation and planning sooner.”
Simio uses discrete-event simulation and advanced planning and scheduling technology to model processes, resources, dependencies, constraints and operational variability. Those models can be used to examine how operations may respond to changes in demand, resource availability and other conditions before decisions are implemented.
The MCP integration gives compatible generative AI applications access to that operational context, allowing users to query a Simio model rather than relying on a large language model’s general knowledge alone.
Aegis is also positioning the capability as a way to shorten the learning curve when employees inherit simulation models developed by other users.
“Understanding what someone else built takes time,” said Gregory Lang, Aegis senior director of engineering and DevOps. “With a compatible AI application connected through Simio’s built-in MCP support, you can quickly see how the model is structured, have its logic explained and ask questions about its behavior.”
The new capability builds on Simio’s existing use of artificial intelligence. Its software includes embedded neural networks that can learn from synthetic data generated during simulation runs and use that information to make runtime decisions within a model.
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