In the race to adopt generative AI, enterprise leaders are discovering a costly reality: what works for a consumer chatting with a bot on their smartphone is often a liability in the call center.
While today’s major speech-to-speech (S2S) models offer impressive fluidity, they operate as opaque black boxes. For heavily regulated industries like healthcare and finance, deploying these models means surrendering control over data, risking compliance breaches, and exposing customers to AI hallucinations. In high-stakes customer service, missing context leads to dead air, abandoned calls, and ultimately, damaged brand reputation and lost revenue.
Now, Rime is offering a fundamentally different approach. Today, the company announced the launch of Prism, the industry’s first fine-tunable, enterprise-grade speech-to-speech model.
Founded in 2022 by a team of voice AI veterans from Stanford and Amazon Alexa, Rime is betting that the future of enterprise AI isn’t about licensing the biggest generalized model. It’s about giving businesses total ownership of their conversational data and infrastructure.
“A generic model with a custom prompt is not your voice. It’s a rental with your logo on it,” says Lily Clifford, Co-founder and CEO of Rime. “Prism is the first speech-to-speech model that becomes yours: it learns from your conversations, lets you set the latency and guardrails, and lives on your infrastructure. Quickly, the model running your calls will be one no competitor can buy.”
Solving the Compliance and Hallucination Headache
For corporate CIOs and customer experience officers, the primary barrier to AI adoption is risk. Prism addresses this directly through a unique “architectural guardrail”: the model generates text before speech.
This seemingly simple structural shift has profound business implications. It allows a company’s internal rules, policies, and safety guardrails to review every single word before the customer actually hears it. For organizations bound by strict regulatory requirements, this text-first approach provides flawless, instantaneous auditability and ensures SOC 2 and HIPAA compliance. Furthermore, businesses can deploy Prism entirely on-premise or within their own private cloud, guaranteeing their proprietary data never feeds a competitor’s model.
But Rime didn’t sacrifice performance for security. Instead of relying on scraped web data, the company built custom recording studios to capture thousands of hours of real, channel-separated human conversations. This proprietary reinforcement learning gives Prism human-grade emotional understanding, allowing it to instantly react to caller frustration, eliminate awkward pauses, and seamlessly route calls to improve containment rates without human intervention.
The ROI of Fine-Tuning: Beating the Tech Giants
In the business of customer service, success is measured in metrics, not hype. To prove Prism’s enterprise viability, Rime pitted a fine-tuned Prism model against OpenAI’s frontier GPT model in a real-world enterprise trial with Revmo.
The business outcomes heavily favored the specialized approach. Prism increased order confirmations and pickup methods to a perfect 100%, compared to just 68% for OpenAI. More importantly for risk-averse brands, Prism increased the number of calls completely devoid of AI hallucinations from 35% to 85%, a staggering 142% improvement over the consumer-grade model. It also significantly reduced conversational lag, jumping from 66% to 88% of calls without dead air.
These metrics are already driving adoption among enterprise leaders. Rime currently automates complex, high-retention calls for industry heavyweights like Asurion, Upstart, and the Mayo Clinic, powering over 100 million monthly interactions.
“Dialpad has been a design partner on Prism from the start,” says Shezan Kazi, VP of AI Products at Dialpad. “We’re looking forward to rolling it out across our agentic products.”
Backed by prominent investors including M13, Twilio Ventures, Corazon Capital, and Unusual Ventures, Rime is proving that in the enterprise AI space, customization and control are the ultimate competitive moats. As companies move past the initial novelty of generative AI, the winners will be the brands that stop renting their voice and start owning it.
