ElevenLabs announced on February 4, 2026 that it raised a $500 million Series D round valuing the company at $11 billion, led by Sequoia Capital with major follow‑on investments from Andreessen Horowitz and ICONIQ. On February 5, 2026, outlets including eWeek and Music Business Worldwide reported the funding as one of the largest private generative‑AI deals to date.
This article aggregates reporting from 3 news sources. The TL;DR is AI-generated from original reporting. Race to AGI's analysis provides editorial context on implications for AGI development.
A $500 million Series D at an $11 billion valuation cements ElevenLabs as one of the most heavily capitalized application‑layer AI companies. The round is explicitly about building “audio general intelligence” and scaling ElevenAgents, its enterprise voice and chat agent platform, which already powers high‑volume interactions for telcos, fintechs and governments. That means a lot more capital going into models and tooling optimized for natural, real‑time human interaction—a capability that will be central to whatever we eventually call AGI.([elevenlabs.io](https://elevenlabs.io/blog/series-d))
Strategically, this funding locks in ElevenLabs as a core infrastructure provider for voice interfaces across consumer apps, enterprise support and creative tools. Its stack—TTS, speech‑to‑text, dubbing, music and agents—sits at the interface layer where humans actually experience AI. As more organizations adopt “voice‑first” and conversational experiences, the company will see a rich stream of behavioral data that can be fed back into increasingly capable dialogue and planning models. That data advantage could become a powerful complement to the compute and model‑scale advantages held by the big labs.
In the AGI race, this round doesn’t move parameter counts, but it does accelerate commercialization of highly naturalistic, emotionally tuned agents. If AI that feels human becomes the default front‑end to many services, the labs and platforms behind those voices will gain enormous influence over how people perceive and trust advanced AI systems—shaping the political and regulatory environment frontier labs operate in.



