Smallest.ai, a voice AI startup, has raised $13 million in a Series A funding round to develop a model that simulates human conversation with minimal delay. The company, founded in late 2024, aims to make AI voice interactions indistinguishable from human conversations. Sudarshan Kamath, the founder and CEO, explained that the model is designed to listen, think, and speak simultaneously, much like how humans process information during a conversation. 'While I’m speaking to you, you’re already thinking, and you might interrupt me if I talk for too long,' Kamath said. The startup’s model serves as a real-time intelligence layer that enables natural customer conversations on specific topics with virtually zero response lag. 'The way an LLM works is you give it an entire prompt, and then it starts thinking,' Kamath noted. While that latency is acceptable in a text chat, in a voice conversation, even a short pause feels unnatural. 'If you think about how we are talking, I’m not giving you like a large clipping of my audio, and then you start thinking.'
Smallest.ai’s model is built to handle voice-specific nuances, such as diverse accents, dozens of languages, and noisy environments. The startup’s existing customers include companies in the voice space, including RingCentral and Truecaller. Kamath said that any customer support company, including newer ones like Sierra and Decagon, is a potential customer for the startup. When asked why a well-funded AI customer support company wouldn’t build its own voice model, Kamath said that for customer support startups, becoming 'extremely good at doing voice is a distraction from their core business.' Smallest.ai competes with voice AI leader ElevenLabs, as well as Cartesia and regional players like Sarvam that focus on local languages. While some competitors apply voice AI to use cases, like audio dubbing and podcasting, Smallest.ai focuses strictly on real-time conversational voice agents for its enterprise customers.
Smallest.ai’s funding round was led by Seligman Ventures with participation from Sierra Ventures and 3one4 Capital. The fresh capital brings the startup’s total funding to over $21 million. Kamath believes that all AI agents will soon rely on two models: a small voice model for real-time interaction, and an 'offline' LLM that is called upon as needed to solve complex problems. 'We want our models to break the Turing test,' Kamath said. 'You should speak to our model and not know it’s AI or human. That’s the sole focus of the company.'
Source: techcrunch
