The duplex speech model for revenue calls. Formerly MetaVoice.
Joined October 2021
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1.8% apart.
We compared Familiar with a human sales rep on outbound lead qualification for PolyborgAI.
We saw similar disqualification and booking rates. Familiar also surfaced insights that helped Polyborg improve its lead targeting.
And it delivered these outcomes at roughly 20x lower cost.
Full results, plus what we're improving next: familiar.io/blog/familiar-vs…
@BMWiVentures is backing Familiar.
What drew us together is a shared belief that the quality of a product is the experience of using it. BMW has built a century of engineering on that idea. It's the same standard we hold for voice interactions with AI. They should feel effortless and familiar, like talking to a person.
That's what we're building: a full-duplex speech model that adapts to how people already speak. It listens while it speaks, and understands not just what was said but how.
Live on revenue calls today.
As Kasper Sage, Managing Partner at BMW i Ventures, put it: "Full duplex is the difference between a demo and a voice agent you can trust in high-stakes workflows."
Read announcement below.
MetaVoice is now Familiar.
Voice AI is growing fast, but most interactions still feel like a walkie-talkie. That's why voice agents today are largely limited to scripted, QA-style conversations.
For voice AI to move beyond that, it has to adapt to the way people already speak. Not the other way around.
Talking to AI should feel familiar, like talking to another person. That is the standard we named the company after.
At the core of Familiar is a full-duplex speech model built to make that possible. It listens while it speaks, for a continuous, two-way conversation.
More on the rename and where we're going: familiar.io/blog/metavoice-i…
Familiar retweeted
I was an early engineer @wayve_ai , building end-to-end AI for self-driving.
The lesson: hand-built pipelines lose to models that learn the whole task.
Voice AI is at the same moment. Every voice agent today is a pipeline: transcribe → think → speak, with a separate component guessing when you're done talking. This turns the conversation into a walkie-talkie exchange, people get frustrated and hang up.
So at @metavoiceio we're building the other thing: one duplex model that listens while it speaks. Calls feel natural, like talking to a person, even through interruptions, overlaps and background voices.
I spoke with Theo @TheBreakAI about my journey, why we're building MetaVoice, how it differs from today’s turn-based solutions, and why revenue calls are the first use case.
youtube.com/watch?v=dy2GTNHZ…
The failures feel small. An awkward pause. A barge-in that’s missed. The agent talks over the caller. The caller corrects a date, but the agent misses it. A voice in the background derails the call.
But these compound quickly and the person gives up.
A model is not production-ready because the demo sounds good.
Developers also need: Control over behavior. Failures they can debug. Calls they can observe. Costs that work at scale.
Mia & Leo are built for that.
Mia & Leo are for developers building inbound and outbound voice agents.
We started with speech that sounds human. Mia & Leo are the next step: speech that can hold a human conversation.
Talk to them at metavoice.io
Familiar retweeted
Natural conversation maxxing!
A sneak peek of @metavoiceio's duplex speech AI.
Launching in 2 weeks.
1/ Our belief @metavoiceio is that voice interactions with AI don’t go far enough.
What if talking to AI felt indistinguishable from talking to a person, even after years of daily interactions? Fluid back and forth, empathetic responses and a consistent personality.
2/ That’s the future we’re building. And we’re fully leaning into the bitter lesson that scalable, data-driven methods win!
Read our blog on the first step towards that: metavoice.io/blog/bitter-les…