Symbolic Logic, Inc. (NASDAQ: EVOL) is a technology firm specializing in advanced mathematical modeling, simulation and digital engineering services for highly complex systems. Founded in 1994 by Dr. Frank O. Starbuck, the company has built a reputation for delivering model-based systems engineering solutions that support critical applications in defense, aerospace, energy and other regulated industries. Its offerings include system architecture design, data analytics, performance modeling and verification using scientific computing tools and high-performance computing platforms.
The company’s core product suite centers on a scalable, web-enabled modeling environment that integrates physics-based simulations with real-time data feeds. Symbolic Logic provides custom software development, technical consulting and training services aimed at improving system reliability, reducing development costs and accelerating time to deployment. Its consultants work closely with clients to tailor model libraries, automate design workflows and perform sensitivity analyses that inform decision-making across the program lifecycle.
Headquartered in San Antonio, Texas, Symbolic Logic maintains additional offices near key federal and commercial clients in the Washington, D.C. and Houston metro areas. The company serves customers in the U.S. Department of Defense, NASA, the Department of Energy and leading private-sector firms in aerospace and industrial automation. Through strategic partnerships and alliances, it also supports international programs requiring rigorous certification and compliance with defense and safety standards.
Symbolic Logic is led by President and Chief Executive Officer Todd F. Johnson, whose more than two decades of experience in digital engineering drives the firm’s innovation roadmap. Chief Financial Officer Michael G. Thompson oversees corporate finance and capital strategy, while Chief Science Officer Dr. Laura M. Patel directs research and development efforts. Together, the leadership team is focused on expanding the company’s cloud-based modeling capabilities and exploring emerging technologies such as artificial intelligence and machine learning to enhance system performance and resiliency.
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