Repath is the deployment safety layer for AI. We believe the biggest unsolved problem in production AI is not capability — it's reliability. AI models break silently, and teams have no safe way to roll out changes.
We built Repath to fix that. A transparent proxy that splits traffic between prompt versions, scores every response with an AI judge, and reverts automatically when quality drops — all before your users notice.
“Make it safe to ship AI. Every team that builds with LLMs should have the same deployment safety primitives that top tech companies use for traditional software.”
We watched GPT-4 drop from 97% accuracy to 2% on coding tasks — silently, with zero API errors. We watched Unity lose $110M from an ML model regression that went undetected. We saw teams discover prompt regressions 34 days after they shipped.
Feature flags solve deployment. Observability tools show you what happened. But nothing existed to prevent quality regressions from reaching users in the first place. That's the gap Repath fills.