URSA Inc.

∙ Reduce Rework – Eliminate manual regression testing that consumes 30–40% of engineering cycles across modernization, porting, and AI-assisted development projects. ∙ Prevent Production Incidents – Prove behavioral equivalence before AI-generated, refactored, or ported code reaches production — in any industry, at any scale. ∙ Ship with Confidence – Give engineering leaders mathematical certainty, not just test coverage, before every significant code transformation. Every software organization is now a code transformation organization. AI coding tools are accelerating how teams write net-new code, refactor legacy systems, and port across languages, platforms, and architectures at a pace and scale no human review process was designed to handle. But the validation layer hasn’t kept up. Tests sample a fraction of possible behavior. Code reviews miss what they can’t anticipate. Static analysis flags syntax, not semantics. No existing tool can prove that transformed code behaves identically to the original across all inputs whether that code was written by a developer, an AI agent, or both. That gap creates a universal risk: behavioral regressions that are invisible until they’re expensive. A financial services firm shipping AI-refactored transaction logic. A healthcare platform porting to a new cloud runtime. An industrial manufacturer modernizing embedded control systems. A SaaS company accelerating feature velocity with AI-generated code. The blast radius differs, but the underlying problem is identical. The result is a forced tradeoff every engineering leader faces: ship fast with unknown behavioral risk, or slow down and test more, knowing you still can’t prove correctness. More AI tooling makes this tradeoff worse, not better. The market needs a verification layer that fits real development workflows: automated, language-agnostic, and capable of returning either mathematical proof of equivalence or actionable counterexamples before risk compounds in production.