Anthropic and Blackstone See AI Implementation as the Next Trillion-Dollar Opportunity

Voice AI companies have found one of their biggest opportunities in helping enterprises automate phone calls across customer service, sales, and marketing. Large organisations are increasingly relying on voice technology providers such as ElevenLabs and Deepgram, infrastructure platforms including Vapi, Retell, and LiveKit, and customer support-focused companies like Decagon and Sierra to manage high volumes of calls.

San Francisco-based Rime is looking to stand out in the increasingly competitive sector by developing voice AI models trained on proprietary conversational datasets that it records itself, reducing the amount of customisation required by enterprise customers.

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

According to the company, its technology is designed to accurately pronounce brand names, company-specific terminology, and industry jargon. Rime uses a phoneme-based architecture that adapts to different pronunciations, allowing customers to avoid retraining models for specialised industries or unique business vocabularies.

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 several others, also participated in the financing.

Clifford said that while voice AI technology has advanced considerably, many enterprises continue to rely on traditional IVR (interactive voice response) systems because today’s AI voice solutions have not yet reached the same level of reliability.

“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 originally built its platform using separate speech-to-text, text-to-speech, and large language models. The company is now transitioning toward speech-to-speech AI models that reduce response latency, improve conversational turn-taking, and better manage challenges such as background noise. This architecture also reduces the need for complex orchestration between multiple AI models.

The startup says its technology is already being used by customers across industries including food service, healthcare, airlines, and financial technology. Rime also claims that its training data and model design help keep callers engaged for longer, contributing to enterprise partnerships with organisations such as Mayo Clinic, Dialpad, Upstart, and Asurion.

With the new capital, Rime plans to expand its 35-person workforce by hiring across engineering, AI model development, and strategic partnerships. The company recently appointed Rafael Valle, formerly part of Meta Superintelligence Labs and Nvidia’s applied deep learning audio research team, as its chief scientist to strengthen its research efforts.

“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,” said Morgan Blumberg of M13.

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