Static cross-file dependency graph construction, leaf-first topological sorting, and automated characterization test synthesis for JavaScript/TypeScript and Python modules.
Company & Engineering Roadmap
Building deterministic infrastructure for legacy software migration
CodeLoom AI was founded to solve one of software engineering's most expensive bottlenecks: migrating business-critical legacy codebases without introducing silent regressions.
Most teams attempting to use general-purpose AI coding assistants for large-scale migrations hit the same wall: rewriting code is easy, but proving that the rewritten code preserves years of subtle production behavior is hard. CodeLoom AI flips the workflow—investing in static dependency graph analysis and automated characterization test synthesis before a single line of legacy code is modified.
Vasil Vasilev
Founder & Lead Systems ArchitectSoftware engineer focused on static program analysis, deterministic verification harnesses, and automated legacy codebase migration.
Engineering Milestones
Pre-launch development roadmap
Automated sandboxed test execution that feeds assertion failures and stack traces back into the transformation loop until the baseline contract passes.
Controlled pilot deployments on bounded production repositories with engineering teams, followed by self-hosted VPC runner packaging.