We were tired of watching agents die in the build-and-pray cycle.
Two builders, twelve years working together, seven of them on the same team shipping machine learning at scale. We kept seeing the same thing: a team commits to building an agent, spends weeks on it, and only meets the failure in production. The cost was set long before anyone wrote a test. That is the moment we decided to own.
Agent failures repeat. We built a layer that recognizes them.
A retry loop in a support agent is the same retry loop in a sales agent. The same shapes, over and over, across every domain.
So we stopped treating each agent as a fresh mystery. Our Pattern Intelligence learns a failure class once and recognizes it everywhere after. That is what lets Faultmap run before the build, on your goal, personas, data, and tools, with nothing to instrument.
No eval tool can take that position. They all start after you have committed. We start one step earlier.
A retry loop in a support agent is the same retry loop in a sales agent. We learn the shape once, then recognize it in your domain before you build.
Builders who lived the problem.
Founder-market fit is direct here, not adjacent. This is a scar, not a slide.
Rengasami Ramanujam
CEO
Spent a decade building machine learning at the scale of tens of millions of users, then led an AI team across three continents shipping enterprise AI. Writes the core engine and the Pattern Intelligence behind Faultmap.
Balagei G Nagarajan
COO
Twenty years running large technical programs, then ran the 120 discovery interviews that found the problem. Handles product, go to market, and the people side. Bootstrapped a business from zero before this one.
We are bootstrapping, on purpose, while we prove the map on real agents with real design partners. We would rather show you a break point than tell you a story.
Faultmap it before you build it.
Run a free map, or talk to us about a build.