The fastest way to lose a client’s trust with AI video is a label that changes from shot to shot. Generated products drift: the logo softens, the cap changes colour, the text turns into something that only looks like text. In product-led films, consistency is not a finishing touch — it is the first thing planned. This is the method I use.
1. Start from the real product
Collect clean packshots from several angles, the label or packaging artwork, logo files and, if it exists, a 3D model. Every later step is checked against these files.
2. Lock the product in keyframes
Before any video, each shot gets a designed still with the product in place — made in an image model such as Nano Banana Pro and corrected until the label is right. A video model is far more reliable when it starts from a correct frame than when it invents the product from text.
3. Give the model references, not adjectives
Models like Seedance 2.0 accept several reference images per generation. Feeding the same product references into every shot keeps shape, colour and proportion stable across the sequence.
4. Keep camera moves kind to the label
Fast rotations, extreme close-ups of small text and hands covering the pack are where drift happens. Plan moves that keep the label readable, and save the hardest angles for 3D.
5. Fix in finishing
Even good takes need checking frame by frame. Small drifts are fixed in compositing — a corrected label tracked onto the bottle, a logo replaced. When a model cannot hold the detail at all, the product is rendered in 3D and placed into the generated scene. The same technique works for bank cards, documents and banknotes in financial ads.
6. Check against the files, not by eye
The final check compares every shot with the original artwork: spelling, logo, colours, proportions. Nothing goes to the client with a misspelt label.
This is the core of the AI product videos I make: the scene can be imagined, the product cannot.
