The improvement layer for production agents

Your agents get better every week.

Ridgeway turns production agent failures into eval-tested fixes. It captures what your agents actually do, triages where they fail, and ships versioned changes that are proven on real traces before they deploy.

Why teams run on Ridgeway

0x

faster from a production failure to a shipped, proven fix

0%

of changes replayed against real traces before they deploy

0

surprise regressions: every change is gated by evals, not vibes

Production is undefeated

One agent in production sets off all of this.

55%

of runs passing evals, climbing version over version. That is the loop compounding: every failure becomes a fix, every fix is proven, and your agents get more accurate, cheaper, and more reliable over time.

The problem

Agents are a new kind of technical debt.

Building agents is becoming the easy part. Keeping them reliable in production is the hard part.

01

They break silently

Agents go stale, drift after model swaps, and fail in weird ways nobody is watching for. The first person to notice is usually a customer.

02

Fixes are guesses

Teams debug by vibes: tweak a prompt, redeploy, hope. Without evals grounded in real traffic, nobody knows if the agent got better or just different.

03

ROI decays

An agent that saved money in month one quietly burns tokens and loses accuracy by month six. Short bursts of productivity, then a slow leak.

You keep building agents. Ridgeway does the ops work: it catches the failures, ships the fixes, and proves every one of them before it reaches production.

How it works

The improvement loop

One line of code to plug in. Then every failure follows the same path back out as a proven fix.

01

Capture

A one-line SDK hook records every LLM call, tool call, and handoff your agents make in production.

02

Triage

Failures cluster themselves by root cause. Fourteen bad runs become one issue with the evidence attached.

03

Fix and prove

Each fix is a versioned change to prompts, tools, or memory, replayed against real past traces before it ships. Pass or it does not go out.

04

Ship and compound

Approved changes deploy and become permanent memory. The agent never fails the same way twice, and every week builds on the last.

Observability tools tell you what broke.
Ridgeway ships the fix and proves it.

Who it is for

Built for teams going agent-native

If your agents handle thousands of runs a week and real customers feel it when they slip, Ridgeway is built for you.

Support agentsBilling and invoice auditClaims processingEnrollment copilotsOps automationsForm-filling agentsSearch and research agentsAnalytics agentsVoice agentsBack-office virtual employees

See the loop run on your agents.

Tell us what your agents do and where they hurt. We will plug in, find the failure patterns, and show you the first proven fix within days.