Current models are expensive, too inconsistent, and force you to iterate at scale just to get the output you want. ORA was trained on more than 50,000 AI UGC videos to produce smoother, more natural, more stable avatars — with economics finally compatible with scale.
When a generation costs too much, you test less. And when you test less, you lose what actually drives performance. ORA was built to break that ceiling.
For months, we have been iterating with our users. The feedback is always the same: too much instability, too much approximation, too much cost to scale AI UGC production with confidence.
A model trained exclusively for marketing avatars and AI UGC. Not to be “good enough.” To produce usable, repeatable creatives that are finally compatible with scale.
If you want to test the model before the full rollout, request access here.
ORA reduces the visual breaks that immediately kill the illusion. The output is cleaner, more stable, and more credible on screen.
No awkward approximation. Voice and mouth sync becomes reliable enough to ship videos you can actually publish.
Facial behavior and gestures align more closely with the codes of high-performing UGC. Less artificial, therefore more usable in acquisition.
The real gain is not just budget. It is the ability to launch 20 variants of the same creative instead of stopping at 3 or 4 tests because you are afraid of burning budget.
The model is currently available on Enterprise plans. Full rollout is planned over the coming weeks, while we finalize the last product and infrastructure adjustments.
If your challenge is producing AI UGC at volume without suffering from the cost of generic models or their instability, ORA is clearly the right move.
Less randomness. More control. A cost structure that finally lets you test, learn, and push your creatives without blowing up your budget.