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Smallest AI
Real-time voice models and an agent platform for enterprise voice AI
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2.3MB · 7,383px tall · uses Times, Geist, Aeonik Medium
Industry
AI Infrastructure, AI Agents, Devtools
Style
Minimal, Bento
Stage
Series A
Built with
Framer
About the site
Smallest AI makes voice models for text-to-speech, speech-to-text and speech-to-speech, plus a platform for building enterprise voice agents. The homepage is almost entirely white and grey, with a single warm orange orb in the hero, and that orb sits inside a tabbed demo: visitors can talk to an agent or switch tabs to try speech-to-text and text-to-speech before scrolling. Further down, a thesis panel argues for many small models over one massive one, model cards quote latency and language counts, a teal speech-to-speech panel shows a live transcript, and a real agent configuration screen and a code snippet close the product case. A clean reference for AI infrastructure sites that let the product do the persuading.
How this page sells
For enterprise voice teams: let buyers call an agent and try each model in the hero, then back it with latency numbers and certifications.
Primary navigation
- Agents
- Models
- Resources
- Pricing
- Sign Up
- Contact Sales
ClickTap a section to see it on the page
'Realtime voice AI suite built for enterprise scale' above a tabbed demo panel for Agents, Speech to text and Text to speech, opening on a 'Talk to an Agent' card with a gradient orb, a Sales Agent named Leo and a Start conversation button.
Why it converts: Each tab is a working demo, so a buyer can talk to an agent and hear the models in the hero before reading any sales copy.
RingCentral, Paytm, Truecaller and Acefone in a single row of black wordmarks.
Why it converts: Two telephony platforms and two consumer apps with huge call and user volumes suggest the models already hold up at enterprise scale.
'We believe AI will evolve like human intelligence. Not one massive model that knows everything but many small ones that each know exactly what matters.' beside stacked essay cards such as 'World Models for Voice'.
Why it converts: A clear research stance explains the company name and presents small models as a deliberate bet on speed and cost, not a compromise.
Three model cards with Get API buttons: Lightning text-to-speech at '100 ms latency across 15+ languages', Pulse speech-to-text in 38 languages, and Electron, 'a sub-3B language model that outperforms GPT-4.1'.
Why it converts: Concrete latency, language and benchmark claims let a technical buyer compare vendors on the page instead of booking a call to find out.
A teal water-texture panel, 'One of the first native speech-to-speech model - built for production', holding a chat transcript that opens 'Hey, I'm Alex from Smallest Kitchen. What's your name?'
Why it converts: Claiming one of the first native speech-to-speech models positions the company at the frontier, and the transcript shows what that sounds like in a real order.
A real configuration screen for a claims intake agent: a system prompt for 'Sarah, a compassionate claims intake specialist', the Electron model, English (UK) and Hindi, and a Robin voice, with Test agent and Publish buttons.
Why it converts: A filled-in insurance agent shows exactly what a buyer would configure, which makes going live feel like an afternoon's work.
A JavaScript snippet calling the lightning-v3.1 endpoint with a voice_id of 'magnus', beside 'Smallest is built for rapid prototyping and seamless integration.'
Why it converts: Copy-paste code turns a developer from reader to tester in minutes, with no sales call in the way.
