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.
We're changing the game for multi-speaker separation in the real world, at scale.
Introducing Luel Multi-Speaker Separation. One messy conversation in. Every voice back on its own track, at up to 48 kHz.
Trained on real conversations from our contributor network of 900k+ users, not just studio speech.
The Luel data marketplace is becoming agent-native.
Buying data is still one of the slowest parts of building — procurement threads, licence review, a sample weeks later. We're taking that friction out.
Now your agent does it. Buy rights-cleared datasets, quality-assured through Luel's QA pipeline.
Have data to sell? Same workflow, same pipeline.
We're launching with our most popular datasets, with regular catalogue updates to follow
Introducing the Luel Speech Platform
Generate production quality speech audio, through our Studio or over the API, with voices from Bhutan to Morocco
Built with Luel's 800,000+ contributor network across 96+ countries.
Your first 30 minutes are included when you sign up ⬇️
Dzongkha TTS — the first commercial-grade voice for Bhutan's national language.
Roughly 600,000 people speak Dzongkha, yet almost no shippable text-to-speech existed for it — digital voices default to English, leaving government announcements, citizen services and everyday interfaces without a natural option.
We're changing that — delivering a voice that reads Dzongkha in Tibetan script, neutral by default with a light emotion layer that shifts warmer or more serious, keeping a Himalayan language audible on the phones, kiosks and learning tools of daily life.
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.