Voice models made for human conversation
Models for the whole conversation
No matter where you are on your voice journey, we have the model you need to keep customers on the line.
Text-to-speech
Voices that keep customers on the line. Fast enough for live calls, with control over accent, pace, and tone.
Speech-to-text
Transcription for live calls. Same key, same deployment, same security review as your voices.
For the calls you can't get wrong
When the voice is talking to a patient, a cardholder, or a hotel guest deciding whether to stay the night, quality stops being a nice-to-have. Rime delivers the speed real conversations need and runs inside your own environment when compliance demands it.
A voice for every conversation
Choose from 600+ voices, then shape accent, pace, and tone until it fits your brand and your industry. What comes out sounds like a person who wants to be on the call and not a system working through a script.
Built by linguists
Rime was founded by people who study how language actually works. That's why our voices land the rhythm, stress, and warmth of real speech instead of the hollow tones you hear everywhere else. We treat voice as a craft, not a feature to bolt onto a stack.
Spoken like a local
From the teams that put us on the line
"Mist v3 on a co-located endpoint has been a 3x latency improvement for us. We're consistently seeing sub-100ms TTFB in production — that's the difference between a conversation that feels human and one that doesn't."
"The latency stays low even under heavy loads. It's a true enterprise production-grade system."
"It was clear that the voice made a real impact on the phone. When guests feel comfortable right away, everything else goes more smoothly."
"In healthcare, the voice is the first point of trust. Patients need to feel heard, not processed — and that starts with how the AI sounds and how fast it responds."
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"Mist v3 is incredibly fast and deterministic pronunciation is a game-changer. When you're powering live conversations at scale, you can't have a model guessing brand names or proper nouns."
