NewWhy we map agent failures before the build, not after
The pre-build AI agent doctor

Find where your agent breaks. From the goal, before you build it.

Pavamana AI Labs is the pre-build AI agent doctor: before you write a line of code, we build a failure map of where your agent will break, prescribe the fix, and forge the agent that passes. No prompts. No traces. No production fire.

Grounded in your goal and your data. No card, no code to start.

Try:
faultmap · your-agent.mapread-only

Goal

Resolve customer support tickets and issue refunds

  • 01

    Read the request

    Scoped, read-only

    Mapped safe
  • 02

    Call the payment or refund API

    Retry loop, no timeout cap

    Likely break
  • 03

    Pass context to the model

    PII leakage vector

    Structural risk
  • 04

    Return the result

    Unvalidated output shape

    Structural risk
  • 05

    Run under load

    No rate-limit handling

    Structural risk

First test suite · generated

  • Payment call: enforce a timeout and cap retries at 3
  • Prompt: redact PII before the model call
  • Output: validate the shape before returning it
  • Backoff and respect provider rate limits
5 steps mapped1 likely break4 tests generated

Preview generated from your goal, in your browser. The full Faultmap runs on your goal, personas, data, and tools.

The shift

Stop building first and praying.

The cost of an agent is set before any tool gets involved. Prototype-and-Pray pays for it in production. Faultmap pays for it in the design phase, for cents.

00Prototype-and-PrayWith Faultmap
01

Build first, meet the failures in production.

See the failures on the goal, before a line of code.

02

Evals run after you have already built the wrong thing.

The check runs before the spend, while it is still cheap.

03

Every new agent relearns the same failures from scratch.

A failure class is mapped once and caught in every domain.

04

Send private goals and data to a frontier lab to find out.

Runs on your side, on your data, before you commit.

05

"Should we build this at all?" costs a burned sprint to answer.

Answered before sprint one, in the design phase.

From goal to shipped

Three steps. One stays free forever.

Start with the map. Take the fix plan when you want it. Hand us the build when it is time to ship.

Faultmap outputsupport-agent
  • 01Read CRM recordMapped safe
  • 02Call refund APILikely break
  • 03Update ticket recordStructural risk
  • 04Hold multi-turn stateLikely break
  • 05Pass context to modelStructural risk
Proof

Two teams are already mapping real agents.

We held one hundred and twenty conversations with the people who build and own agents. The answer was the same almost every time. Kezzler and BuSoft are now running Faultmap on agents headed for production, before the build.

Kezzler logo

Kezzler

BuSoft logo

BuSoft

Runs before the tools you already use

LangSmithGalileoPatronusBraintrustArizeLangfuseHeliconeDatadog

Every eval and observability tool starts after you build. Faultmap starts one step earlier.

Questions

The skeptical builder questions.

The pre-build AI agent doctor. We map where your agent will break before you build it, prescribe the fix, and forge the agent that passes.

A failure map of where your agent breaks, plus the first test suite it has to pass, generated from your goal and data before any code.

No. It is built for the pre-build moment, where a fix costs cents instead of thousands. The same failure-pattern library also diagnoses and fixes agents already breaking in production.

They start after you build. We start before. We map where the agent breaks before a line of code exists.

It runs on your side in the design phase. No code, prompts, or traces leave your environment.

Faultmap it before you build it.

Get the map of where your agent breaks, and the first test suite it has to pass, before you write a line of code.