AI video localization, dubbing and translation platform for creators and global teams
Transform text descriptions into high-quality professional videos using advanced AI
Stage
Not given
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Founded
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Based in
HK
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Pricing model
Freemium
Freemium
Pricing
Free trial credits available. Pay-as-you-go option, monthly subscriptions, annual subscriptions, and enterprise plans. Standard translation costs approximately 60 credits per 1 minute of video. Lip-sync feature adds an additional 60 credits per minute.
Hobby $7.92/month (200 Credits/month), Basic $15.92/month (500 Credits/month), Pro $39.92/month (2000 Credits/month), Lite $5.99 one-time (50 Credits). 1 credit generates 1 AI artwork.
Key features
Support for 170+ languages and regional accents
AI voice dubbing and voice cloning
AI-powered lip-sync matching mouth movements
Multi-speaker identification and assignment
Advanced editing studio with unlimited edits
Bilingual subtitle generation and translation
Glossary and pronunciation control
Batch processing and automation
Supports videos up to 2 hours in length
Advanced 30-billion parameter AI model for detailed video generation
Generate videos up to 204 frames long
Video-VAE deep compression technology for faster processing
High-quality visual output with DiT and 3D Full Attention mechanism
Bilingual text input support for English and Chinese
Customizable video length and style settings
No ads and no watermark on generated videos
Priority generation queue for faster processing
What makes it different
Video-first approach combining translation, dubbing, and lip-sync in a single workflow
Works exceptionally well with low-resource and underrepresented languages
Unlimited edits without consuming additional credits after purchase
Native speaker collaboration for quality assurance across all languages
Enterprise infrastructure with managed delivery and QC workflows
Supports up to 204 frames, enabling longer and more complete video narratives
Bilingual AI understanding for both English and Chinese creators
Continuous optimization through human feedback-based preference learning