Mati Staniszewski
Co-founder and CEO of ElevenLabs, an applied AI company building voice, speech, dubbing, and conversational audio tools. Staniszewski leads teams developing AI systems that communicate at a human level, after earlier roles at Palantir, BlackRock, and Opera Software.
London AI Founders Are Building Global Companies From Britain
ElevenLabs chief executive Mati Staniszewski told Bloomberg that London’s AI ecosystem has moved beyond a talent story and is becoming a credible base for building global companies. Speaking at London Tech Week, he argued that returning talent, greater founder risk appetite and more willingness from UK and European customers to buy from young AI companies are reinforcing that shift. ElevenLabs, the UK-founded voice AI startup valued at about $11 billion, is presented as both evidence and beneficiary of the change.
ElevenLabs Unveils Dubbing v2 and Previews More Controllable Eleven v4
ElevenLabs co-founder Mati Staniszewski used a Warsaw summit keynote to argue that AI’s next constraint is not intelligence but communication people can trust. He presented two new models — Dubbing v2, designed to preserve an original performance across languages, and a preview of Eleven v4, aimed at finer control over speech, emotion, accent, whispering and song — as evidence of that thesis. The broader case was that voice AI becomes commercially useful only when models are tied to agents, integrations, authentication, memory and deployment systems that let companies put spoken interfaces into production.
Voice Will Be the Primary Interface for AI Agents and Robots
At Sequoia’s AI Ascent 2026, ElevenLabs co-founder and CEO Mati Staniszewski argues that audio was an overlooked frontier in 2022 because the AI field was focused on text and images, leaving room for a smaller company to build quickly and monetize early. His broader case is that as AI intelligence becomes more capable, voice becomes the interface problem: the way people will use agents, robots, services, education and healthcare. Staniszewski says the next hard problems are emotional intelligence, timing, authentication and workflow, not merely making synthetic speech sound human.