We learned the hard way how invisible agent failures are. So we built Voxmith.

We are a small, remote team of engineers and researchers who shipped AI agents into production, watched them fail in ways no dashboard could explain, and decided to fix the tooling instead of guessing.

Where we come from

Our founders built conversational AI for support and sales teams, in environments where a single bad interaction costs real money and real trust. We shipped agents, watched them handle thousands of live conversations, and then spent weeks reading transcripts trying to work out what went wrong.

The lesson was uncomfortable. Logs tell you what an agent said. They never tell you why a user hesitated, interrupted, repeated themselves, or quietly gave up. The failures that matter most are the ones that leave no error in the stack trace.

So we built Voxmith: step-by-step tracing for every voice and chat conversation, with failures surfaced the moment they happen and every recommendation backed by production evidence. The tool we wished we had, built for the teams still guessing.

Our journey so far

From a shared frustration to a platform trusted by teams running agents in production.

2024

The problem finds us

While building voice agents for support teams, we kept hitting the same wall: no visibility into why conversations failed. Logs told us what happened, never why.

Early 2025

First traces, first customers

We shipped step-by-step conversation tracing to five design partners. Within a week they found drop-off patterns that had been invisible for months.

Late 2025

From diagnosis to fix

Failure detection grew into engineering recommendations. Every issue now ships with production evidence attached and a one-click path to a PR or ticket.

Today