Rime raised $24 million in Series A funding led by M13 Ventures to build voice AI models that handle enterprise customer calls.

The San Francisco startup competes in a crowded market alongside ElevenLabs, infrastructure companies like Vapi and Retell, and customer support specialists like Decagon and Sierra. Rime differentiates itself by training models on proprietary conversational data recorded in its own studio rather than scraping web audio.

Founded in 2022 by former Stanford PhD student Lily Clifford, ex-Amazon Alexa engineer Brooke Larson, and Stanford engineer Ares Geovanos, the company built a recording facility to collect conversational data. This approach aims to reduce client customization requirements.

Rime focuses on tuning voice models for accurate pronunciation of brand names and industry-specific terminology. The startup employs a phoneme-based architecture that adapts to different pronunciations without requiring customers to retrain models for their sector.

Twilio Ventures, Corazon Capital, Unusual Ventures, and existing investors joined the round. The company handles over 100 million calls monthly across multiple enterprise clients.

"The voice technology is still not there to automate the vast majority of enterprise phone calls," said CEO Clifford. "LLMs have made it a lot easier to build voice applications that work, but they haven't changed how it feels to interact."

Rime initially used separate models for speech-to-text, text-to-speech, and language processing. The company is now developing integrated speech-to-speech models to reduce latency and improve conversation flow.

The funding will support expansion of Rime's proprietary data collection and model development as enterprises increasingly adopt AI voice solutions for customer service operations.