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Bolstering Commander's Omniscience through MBSE

Developing software solutions to drive digital transformation


CIMBEO–which stands for Commander’s Intent Model Based Engineering Options–was developed by Willowview as part of the United States Special Operations Command’s (SOCOM) Science & Technology Directorate Futures event, a 6-month prototyping event which aims to explore high-risk, high-reward technologies to be employed by US Special Operations Forces in a future operating environment.

Our Approach

CIMBEO leverages SysML and modern model-based systems engineering (MBSE) tools to assist in the military decision-making process. By modeling the structure, behaviors, parametrics, and requirements of a mission based on the Commanders Intent, we quickly create and simulate courses of action (COAs) to meet the needs of operators, mission planners, and high-level strategists.


Our Future

By leveraging MBSE principles to streamline mission planning, our goals are to enable CIMBEO to be applied to any mission set, implement machine learning and AI tools to improve the simulation speed, and reduce the time, money, and resources mission planners spend gathering and parsing large amounts of data.

How CIMBEO Works

Utilize COTS MBSE tools to model a mission

After inputting specific mission constraints, available assets and mission goals, a set of experiments is rapidly designed and simulated thousands of times to determine which available asset results in the highest likelihood of success. These qualities greatly increase the confidence and rigor behind the mission plan and give our forces a competitive edge in reducing the fog of war. 

Maximize automation, explainability, and rigor with MBSE techniques

We believe innovative software development requires a collaborative approach. We work closely with our clients to gain a deep understanding of their business needs and goals then use that knowledge to develop tailored solutions to meet their unique requirements.

Optimize COAs with statistical analysis

Easily change the variables to measure the modified outcome of the mission with Monte Carlo simulations quickly, saving time and resources and preventing running the mission requirements from scratch with each suggested change.

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