Familiar
Familiar is a YC Summer 2026 (S26) company. Based in Toronto, ON, Canada. Team of 7.
About Familiar
Summary
Familiar builds an AI dubbing system that translates video content across 99 source languages into 30 output languages while preserving each speaker's voice, face, lips, and delivery. A single proprietary diffusion omni-model processes voice, person, and scene together, replacing the patchwork of separate models and manual pre-processing that rivals and human dubbing pipelines depend on. The target customers are movies and TV studios, broadcasters, education platforms, and ad teams that need localized content at scale without losing the original performance.
Business model
API access, with a team-contact sales path for larger customers.
Go-to-market
Content producers in film, TV, broadcast, education, and advertising are the buyers; they can access the product via API or by talking directly with the team.
From the Y Combinator listing
Dubbing is finally good. Audio-Visual Translation.
World models for accurate humans. 🦋 Content in every language. The speakers' performances, preserved. Movies & TV, Broadcasts, Education, Ads, Platforms, Live Shopping. Founders An Zhu Liu, Mingi Kwon, and Xu Zheng lead a team of PhDs, professors, and researchers from the world's top universities who started the field of joint audio-visual human models and co-authored the current state of the art in real-time human animation. They started with video language translation, and they've already built one of the most accurate translators available today, the only one that works in real time. Everyone else scaffolds separate models and pre-processing; a world model just understands -- what the speaker means, from voice, person, and scene together. That's why the dub keeps the speaker's own voice, face, and delivery. Vs ElevenLabs: they lose the laughter, the music, the ambiance -- 270% more background-sound error -- and ours sounds 27.8% more like you. Vs human translators: 100.3% of their quality -- scalable, real time. Published benchmarks: https://thefamiliarlab.com/benchmark The $14B spent on dubbing every year flips to AI once it's good enough -- most of it movies and TV, the traditional dubbing heartland. Live multiplies it.
Facts
- B2B / B2B -> Infrastructure
- Toronto, ON, Canada
- 7
- Active
- Early
Founders (1)
- Mingi Kwon
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