Maestro reads every production call, finds the failure patterns that keep repeating, and proposes the exact change to your flow. You review a diff. You click apply. The fix is gated against your regression suite before it ever reaches a caller.
A caller says something unexpected. Someone listens to the recording three days later, guesses at a cause, adds a sentence to a 4,000-word system prompt, and hopes nothing else broke. There is no measurement, no gate, and no way to know whether the fix held.
Optimizing against raw call outputs alone will drift you confidently in the wrong direction. Maestro grounds every proposal in a regression suite built from your own production failures, so a fix has to prove itself before it ships.
Continuous evaluation runs on live traffic against the outcomes you care about: containment, correct data capture, policy adherence, escalation reason. Manual QA reaches a few percent of calls. This reaches all of them.
Per-call dashboards are commodity. The useful unit is the recurring failure mode — grouped, named, and ranked by how often it happens and what it costs. Nobody should be handed a blank text box and asked what's wrong.
Most fixes get aimed at the prompt because that's the only editable surface. Maestro decides whether the fault is in the flow graph, the tool contract, the prompt, or the audio pipeline — and routes the fix there.
Reflective optimization proposes a candidate change and tests it against a disposable copy of your agent. Your production flow is never the experiment. The output is a reviewable diff, not a silent rewrite.
Every past failure becomes a permanent test case. A proposal only reaches you if it fixes the target pattern and holds every case that already passed. The same bug can't ship twice.
Applied changes are tracked against their projection. If the real outcome misses the forecast, the change log gives you a one-click revert with full attribution of what changed and why.
Research on enterprise conversational agents keeps landing on the same taxonomy, and three of the four dominant classes are structural. You cannot fix a sequencing bug with an adjective. Maestro sends each class to the layer that owns it.
The agent proceeds without invoking a required tool, so downstream steps run on unverified state.
The agent performs the right steps in the wrong sequence, producing a valid-looking call with an invalid outcome.
The agent shortcuts to a terminal state, skipping the intermediate work that made the call worth automating.
The agent ignores an explicit constraint it was given. This one genuinely is a prompt problem — and it's the minority case.
of production issues in voice AI are voice-specific — latency, barge-in, accent handling, background noise. They are invisible to any team evaluating transcripts alone, and no amount of prompt rewriting will touch them. Maestro scores the audio layer as a first-class signal, so a latency regression doesn't get misdiagnosed as a wording problem.
The underlying capability is identical either way. Only the trust posture changes — and in banking, insurance, and servicing, the trust posture is the product. Four guarantees, on by default.
Optimization runs against a disposable clone of your agent, tools and all. Your production flow is untouched until you say so.
Every proposal shows exactly which nodes, guards, and instructions change — before it lands, in the same view where you approve it.
Choose per category. Let copy fixes apply automatically; hold anything that touches compliance language or call routing for review.
A change log records what was applied, what it projected, and what it actually did. Revert any change with attribution intact.
Fixing your flows requires understanding every conversation. Understanding every conversation gets you something bigger: a continuously updated picture of each customer, assembled from every channel they touch.
Start with agents that maintain themselves. Grow into one profile per entity that every channel writes to and every workflow reads from.
We're taking on a small number of design partners in commercial banking, P&C insurance, and mortgage servicing. Give us read access to two weeks of calls and we'll show you the failure patterns you're not seeing — before you commit to anything.