Conversor · Beta

Know your voice agent works before a real caller finds out it doesn't.

Author the conversation logic your agent runs, then test it against real, varied input. Ship what you've proven, not what you're hoping works.

Private beta · No credit card · Invite-only

Pass or fail, before it ships
The Conversor editor showing an Opening & Rapport phase with two interventions, two constraints, and a progress gate with pass and fail criteria.

It's not the model. It's the conversation logic.

The model handles language fine. What breaks is the flow underneath it: the assumption that callers answer on topic, in order, on the first try. Real callers don't. That's the part that has to be tested, and usually isn't.

How it works

Author it, then prove it.

Design the flow, then run it against the cases it actually has to handle, one section at a time.

01 · Author

Design the flow.

Drag phases onto a timeline. Add the questions, statements, and follow-ups you want the agent to use. No code.

02 · Test

Run it against real cases.

Pick a section and throw scenarios at it: the odd phrasing, the out-of-order answer, the case you're worried about. Change one section, re-test just that section.

03 · Catch

See exactly where it breaks.

When a case fails, you see exactly which part of the flow mishandled it, not just that something went wrong. Fix it and run it again.

04 · Ship

Go live with evidence.

Export the finished, tested flow as a prompt for Claude, GPT, or any model. You shipped what you proved, not what you hoped. Pipecat, Parlant, and Vapi are next.

Under the hood

You see exactly where the logic breaks.

Every phase ends with a Progress Gate: pass criteria and fail criteria, written by you. Run a scenario through it and the gate shows you exactly where the logic held and where it didn't. That's the difference between a call that looks fine and one you've actually proven works.

Who it's for

For agents that have to hold up, not just demo well.

You're building a conversational voice AI agent. Technical enough to deploy it, not necessarily technical enough, or willing, to hand-code every conversational flow. What has to hold up isn't the model. It's the conversation logic, under real, varied input, not just the happy path from a demo.

Get your beta invite.

Conversor is in private beta. Drop your email and we'll send an invite as seats open.

No credit card. No calendar bookings. Just an invite when your seat opens.

Thanks. You're on the list.

Check your inbox for confirmation. We'll send an invite as soon as your seat opens.

FAQ

Questions, answered.

Does this work with my existing AI stack?

Today, Conversor exports a structured system prompt that works with any LLM: Claude, GPT, Gemini, Llama, local models. Direct integrations with voice runtimes (Pipecat, Parlant, Vapi) are on the near-term roadmap.

Do I need to know how to code?

No. Conversor is a visual editor end-to-end. If you can drag a card and type in a box, you can design a conversation.

Is my data private?

Your conversations are scoped to your account. We don't train on your content. Individual accounts today; team workspaces coming.

What does it cost?

Free during beta. Pricing will land with general availability.