
Rime picks up $24M Series A to help enterprises field customer calls
Quick Answer
Rime, a voice AI startup, has raised $24M in Series A funding to enhance enterprise call handling with its proprietary models trained on conversational data.
Quick Take
Rime, a voice AI startup, has raised $24M in Series A funding to enhance enterprise call handling with its proprietary models trained on conversational data. Founded by ex-Stanford and Amazon engineers, Rime aims to improve customer interaction by reducing customization needs and focusing on speech-to-speech models to enhance performance in regulated environments.
Key Points
- Rime's voice AI models are trained on proprietary conversational data.
- The startup aims to improve speech-to-speech interactions to reduce latency.
- Rime has secured enterprise contracts with clients like Mayo Clinic and Dialpad.
- The recent funding will expand Rime's team and enhance model development.
- M13 Ventures led the $24M Series A funding round.
📖 Reader Mode
~3 min readVoice AI startups’ biggest unlock has been handling calls for enterprises in areas like sales, marketing and customer support. Large organizations are offloading calls to voice model developers like ElevenLabs and Deepgram; infrastructure companies like Vapi, Retell, and LiveKit; and dedicated customer support shops like Decagon and Sierra.
San Francisco-based Rime is trying to gain an edge in this crowded market with its voice AI models that are trained on conversational data that it records, aiming to reduce its clients’ customization load.
Founded in 2022 by former Stanford PhD student Lily Clifford, ex-Amazon Alexa engineer Brooke Larson, and Stanford engineer Ares Geovanos, Rime has built a recording studio in San Francisco to collect its own conversational data rather than relying on scraping the web for audio.
The startup said it focuses on tuning its voice models to nail the pronunciation of different brand entities and industry-specific terms. It employs a phoneme-based architecture to adapt to different pronunciations so that customers don’t have to retrain models for their specific industry.
Rime on Wednesday said it has raised $24 million in a Series A funding round that was led by M13 Ventures. Twilio Ventures, Corazon Capital, Unusual Ventures and other existing investors also participated.
Clifford said that despite progress in voice AI development, enterprises still prefer legacy IVR implementations, as AI voice technology still can’t match up to IVR’s 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.
The startup started off with a pipeline of separate models for speech-to-text, text-to-speech, and a large language model. But it is now shifting focus to develop better speech-to-speech models to reduce latency, improve turn-taking, and tackle issues like background noise. The new approach will also serve to decrease reliance on orchestration, so the company doesn’t have to manage a bunch of models.
Rime says it has customers in food service, healthcare, airlines, and fintech. The company claims that because of its training data and model positioning, customers stay longer on the call, which has helped it win enterprise contracts from clients like Mayo Clinic, Dialpad, Upstart, and Asurion.
With the new funding, Rime is planning to expand its team of 35 people, aiming to hire for model development, engineering, and partnerships. It recently brought on Rafael Valle, who worked on audio understanding at Meta Superintelligence Labs and NVIDIA’s applied deep learning audio research team, as its Chief Scientist.
“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.
It had previously raised $5.5 million in a seed round last May. Blumberg is joining the startup’s board as part of the fundraise.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Ivan covers global consumer tech developments at TechCrunch. He is based out of India and has previously worked at publications including Huffington Post and The Next Web.
You can contact or verify outreach from Ivan by emailing im@ivanmehta.com or via encrypted message at ivan.42 on Signal.
— Originally published at techcrunch.com
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from TechCrunch
See more →
OpenAI launches its new family of models with GPT-5.6
OpenAI has launched GPT-5.6, featuring three models: Sol, Terra, and Luna, with Sol being 54% more token efficient for coding tasks. The models excel in cybersecurity and enterprise applications, outperforming competitors like Anthropic's Fable in benchmarks. Pricing starts at $1 for Luna and goes up to $30 for Sol per million tokens.

