Speedscale

Speedscale addresses the 'validation gap' in AI-assisted software development by providing runtime validation for code generated by AI agents like Claude Code, Cursor, Copilot, and Codex. It captures real production traffic patterns and replays them against AI changes in deterministic sandboxes, identifying behavioral failures that static analysis tools cannot detect. This ensures that AI-authored code behaves as expected in a production environment before it is merged. The platform is designed for development teams and platform engineers who are integrating AI coding tools into their workflows. It helps them confidently ship AI-assisted releases by providing proof of code behavior based on repeatable requests and responses. Speedscale reduces the need for manual review of large AI-generated codebases and eliminates the burden of constantly rebuilding or babysitting staging clusters. Key benefits include catching regressions early, ensuring contract adherence, and providing audit-ready evidence for every pull request. It allows engineers to surface exact requests that an AI-generated change broke, compare performance metrics like latency and retries, and share traffic snapshots with AI agents for reproduction of defects with production context, all without exposing sensitive production data.