Luel

There’s only so much AI can learn from the public internet. Some of the harder problems require data people have to create. When we invested in Luel, we believed the next generation of AI would need high-quality human data grounded in the real world. With Luel Labs, William Namgyal and Inigo Lenderking are taking the human-data infrastructure they’ve built at Luel into multimodal research, starting with speech and underrepresented languages where existing datasets fall short. We’re excited to see where William, Inigo, and the team take Luel Labs.

Today we're launching Luel Labs, our end-to-end multimodal data lab. Our research is powered by Luel's global network—leveraging 750,000+ contributors across 96+ countries to generate fully consented, quality-assured audio, video, and image data. First up — Breakthrough TTS for underrepresented languages from the tips of the Himalayas and across the Sahara. We're delivering the first commercial-grade TTS for Tibetan and Dzongkha, and outperforming existing Masri and Darija models. Alongside this effort, we’re driving foundational research to help the industry handle messy, real-world data—pioneering new approaches to 48kHz speaker separation, conversational overlap, STT modeling, data integrity, speech understanding and more.

AI is being built in a few hundred languages. The world speaks around 7,000. That gap isn't only about voice technology. It's about who gets served by the systems now shaping how people access government, healthcare, education, and work — and who gets left out because the technology never learned their language. The people in this film speak languages most technology hasn't reached. They're not hidden from the world. They're hidden from the technology shaping its future.

Today we're launching Luel Labs, our end-to-end multimodal data lab. Our research is powered by Luel's global network—leveraging 750,000+ contributors across 96+ countries to generate fully consented, quality-assured audio, video, and image data. First up — Breakthrough TTS for underrepresented languages from the tips of the Himalayas and across the Sahara. We're delivering the first commercial-grade TTS for Tibetan and Dzongkha, and outperforming existing Masri and Darija models. Alongside this effort, we’re driving foundational research to help the industry handle messy, real-world data—pioneering new approaches to 48kHz speaker separation, conversational overlap, STT modeling, data integrity, speech understanding and more.