Smallest.ai Raises $13M to Build Faster, More Human-Sounding Voice AI

Smallest.ai has raised a $13 million Series A round led by Seligman Ventures, with participation from Sierra Ventures and 3one4 Capital. The round brings the startup’s total funding to over $21 million.

The company, founded in late 2024, is focused on making AI phone conversations feel indistinguishable from speaking with a human. Its core bet is that better voice agents require smaller, specialized models rather than simply faster large language models.

Smallest.ai is developing a voice model designed to mimic how people listen, think, and speak at the same time. The aim is to reduce the response lag that can make AI voice agents feel unnatural in customer support interactions.

The model acts as a real-time intelligence layer for conversations on specific topics. When a request falls outside its knowledge base, Smallest.ai hands the query to a larger foundational model and briefly places the customer on hold, similar to how a human agent might research an issue.

Voice AI is increasingly capable of solving support problems, but callers can often still tell when they are speaking to a machine. Smallest.ai’s pitch is that enterprises need models tuned for voice-specific challenges, including accents, dozens of languages, and noisy environments.

The company already counts RingCentral and Truecaller among its voice-space customers. CEO Sudarshan Kamath also sees customer support companies, including Sierra and Decagon, as potential customers because building advanced voice capability can distract from their core business.

Smallest.ai competes with ElevenLabs, Cartesia, and regional players such as Sarvam. While some voice AI companies focus on areas like audio dubbing and podcasting, Smallest.ai is concentrating on real-time conversational voice agents for enterprise customers.

The company’s stated goal is to build models that can pass a Turing-test-like standard in phone calls: users should not know whether they are speaking with AI or a human. That focus gives the startup a clear lane, but also puts it in a fast-moving and crowded voice AI market.