AI is transforming software development, but it's also creating a correctness crisis. As AI generates code at unprecedented scale, we apply formal methods to verify software behavior before it reaches production —giving companies the confidence, compliance, and speed to ship what's proven, not assumed.
Code at AI Scale.
Correctness Without Compromise.
Ship What’s Proven, Not Assumed.
• Reduce Rework – Dramatically eliminate manual regression testing during modernization.
• Prevent Production Incidents – Prove behavioral equivalence before AI-generated software reaches production.
• Improve Engineering Velocity – Refactor and modernize large codebases faster with automated verification.
Software teams are increasingly using automation and AI to rewrite, refactor, and port large codebases, but existing validation methods (tests, reviews, static analysis) often cannot prove that transformed code is behaviorally equivalent to the original across all relevant inputs.
This creates a high-cost bottleneck: organizations must choose between shipping quickly with uncertain risk or slowing delivery to reduce uncertainty. The challenge is especially acute in large modernization and porting projects, where manual verification does not scale and subtle behavioral regressions can be expensive, unsafe, or compliance-critical.
The market needs practical formal assurance that fits real development workflows and provides either mathematical equivalence or actionable counterexamples early in the lifecycle.
* Awarded a DARPA contract supporting 12 months of full-time commercialization effort following selection into DARPA’s Embedded Entrepreneur Initiative (EEI); working with Capital Factory and a DARPA Senior Commercialization Advisor (SCA) to accelerate FMToolkit go-to-market and customer traction.
* Selected for and completed MassChallenge’s Security & Resiliency program, expanding our commercialization network across government, enterprise, and investor ecosystems.
