Rime Launches Prism Speech to Speech Model With 300 Millisecond Response Time and Reinforcement Learning Customization
introducing prism, the world’s first speech-to-speech model you can’t tell from a human in conversation prism has: > 300ms response time, 4x faster than OpenAI GPT-Live > outperforms every other s2s model on intelligence (with NO reasoning) > the first s2s model customizable through reinforcement learning we’re a team of 35 with $35M in funding, and we’re unlocking s2s model adoption faster than openai, google, and x. the first 100 people to sign up here get 1 month free:
Context
By combining 300 millisecond latency and reinforcement learning customization with an intermediate text checkpoint before audio playback, Rime gives regulated enterprises a speech to speech voice model that preserves caller tone while still enforcing policy guardrails.
Voice AI startup Rime, known for its low latency Coda and Mist conversational voice synthesis models, built Prism with a 35 person team and 35 million dollars in funding to target high volume enterprise voice agent deployments.
Deep dive
Rime founder and CEO Lily Clifford introduced Prism, a speech to speech model engineered for real time human conversation and enterprise customer service calls. Clifford reported that Prism achieves a 300 millisecond response time, four times faster than OpenAI GPT Live, and places first in accuracy and latency on the Artificial Analysis Tau Voice benchmark without turning on extended reasoning.
Unlike traditional cascaded pipelines that transcribe audio to text and lose vocal inflection, Prism reasons directly over raw caller audio to capture tone alongside words. Before generating speech, however, the model emits text as an output checkpoint so enterprise applications can verify every response against compliance policies, guardrails, and required legal disclosures before the caller hears a word. Rime also introduced reinforcement learning customization that trains Prism directly on an organization's own historical call recordings.
Built by a 35 person team with 35 million dollars in funding, Prism supports cloud, virtual private cloud, and on premises deployments with HIPAA and SOC 2 compliance. On its launch page, Rime shared production results with Dialpad, Twilio, and ordering agent provider Revmo, where fine tuning Prism on ten hours of production calls increased orders placed with explicit caller consent to 94 percent compared to 57 percent using an OpenAI model.
What to expect next
Rime plans to publish full developer documentation for Prism while onboarding initial signups through its self serve portal and expanding production deployments with design partner Dialpad and enterprise call centers. As voice agents move deeper into regulated financial, healthcare, and customer ordering workflows, audio native models that expose a verifiable text checkpoint and run on premises will compete directly with cloud only frontier voice APIs from OpenAI and Google.