Rime Raises $24 Million Series A to Expand Enterprise Customer Call AI Platform

Voice AI startups have found one of their biggest opportunities in handling enterprise phone calls across customer support, sales, and marketing. Large organisations are increasingly outsourcing voice interactions to AI model providers such as ElevenLabs and Deepgram, to infrastructure companies including Vapi, Retell, and LiveKit, and to customer service-focused platforms like Decagon and Sierra.

San Francisco-based Rime aims to distinguish itself in this competitive market with voice AI models trained on proprietary conversational datasets it records internally, reducing the amount of customisation enterprise customers need before deployment.

Founded in 2022 by former Stanford PhD student Lily Clifford, former Amazon Alexa engineer Brooke Larson, and Stanford engineer Ares Geovanos, Rime has established its own San Francisco recording studio to capture authentic conversational speech rather than relying on audio scraped from the internet.

The company says it specialises in optimising its voice models to pronounce brand names and industry-specific terminology accurately. By using a phoneme-based architecture, Rime enables its models to adapt to different pronunciations without requiring customers to retrain them for individual business sectors.

On Wednesday, Rime announced it had raised $24 million in a Series A funding round led by M13 Ventures. Existing investors, including Twilio Ventures, Corazon Capital, Unusual Ventures, and others, also participated in the financing.

Clifford said that although voice AI has advanced considerably, many enterprises continue to rely on traditional IVR (interactive voice response) systems because current AI voice technology still falls short of matching the consistency and reliability of legacy solutions.

“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.

Rime initially built its platform using separate speech-to-text, text-to-speech, and large language models. The company is now shifting toward developing more advanced speech-to-speech models that aim to reduce response latency, improve conversational turn-taking, and better handle background noise. The new architecture is also expected to reduce reliance on complex orchestration between multiple AI models.

According to the company, its customer base spans industries including healthcare, food service, airlines, and financial technology. Rime says its proprietary training data and model design help keep callers engaged for longer, contributing to enterprise contracts with organisations such as Mayo Clinic, Dialpad, Upstart, and Asurion.

With the fresh capital, Rime plans to expand its 35-person workforce by hiring additional talent across AI model development, engineering, and strategic partnerships. The company also recently appointed Rafael Valle, formerly of 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 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 said.

Before this latest funding round, Rime had raised $5.5 million in seed financing last May. As part of the Series A investment, Blumberg will also join the company’s board of directors.