Rime lands $24M to remake enterprise call handling

Rime raises fresh capital for enterprise voice calls

Rime, a San Francisco-based startup building voice models for enterprise phone calls, said Wednesday it has raised $24 million in a Series A round led by M13 Ventures.

Twilio Ventures, Corazon Capital, Unusual Ventures, and other existing investors also participated. Morgan Blumberg of M13 is joining the company’s board as part of the fundraise.

The company was founded in 2022 by former Stanford PhD student Lily Clifford, ex-Amazon Alexa engineer Brooke Larson, and Stanford engineer Ares Geovanos.

Betting on its own data

Rime is entering a crowded market for enterprise voice tools, where companies are turning to model developers like ElevenLabs and Deepgram, infrastructure providers such as Vapi, Retell, and LiveKit, and customer support specialists including Decagon and Sierra.

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Its pitch is that it can reduce the customization work required by enterprise customers. Rather than scraping web audio, Rime built a recording studio in San Francisco to collect its own conversational data.

The startup said it tunes its voice models to better pronounce brand entities and industry-specific terms. It uses a phoneme-based architecture to adapt to different pronunciations, with the goal of letting customers avoid retraining models for each vertical.

Why Rime thinks the tech still falls short

Clifford told TechCrunch that even with recent progress, many enterprises still favor legacy IVR systems because voice systems still do not match IVR’s reliability and effectiveness.

“The voice technology is still not there to automate the vast majority of enterprise phone calls. LLMs have made it a lot easier to build voice applications that work, but they haven’t changed how it feels to interact. Talking with a voice AI agent is not the most compelling experience for the end user. It’s kinda like a new IVR, but with a better voice,” she said.

That view helps explain Rime’s product shift. The company began with a stack of separate models for speech-to-text, text-to-speech, and a large language model, but it is now focusing on speech-to-speech models.

According to the company, that change is meant to:

• reduce latency
• improve turn-taking
• handle background noise better
• cut reliance on model orchestration

Customers and hiring plans

Rime says it has customers across food service, healthcare, airlines, and fintech. It claims its training data and model approach keep customers on calls longer, helping it land enterprise contracts with Mayo Clinic, Dialpad, Upstart, and Asurion.

With the new funding, the company plans to grow beyond its current team of 35. Hiring will focus on model development, engineering, and partnerships.

Rime also recently hired Rafael Valle as chief scientist. Valle previously worked on audio understanding at Meta Superintelligence Labs and on NVIDIA’s applied deep learning audio research team.

Investor view

Blumberg said Rime stands out as some competitors push further up the stack.

“Companies like ElevenLabs have moved into being an orchestration and the application layer, going head to head with the Sierras and Decagons of the world. I think there’s just so much more to be done technically, and Rime’s approach of pushing forward on the best model with low latency and high reliability in a regulated environment stands out,” M13's Morgan Blumberg told TechCrunch.

Before this round, Rime had raised $5.5 million in a seed round last May.