Custom models
Your brand's model. Your brand's moat.
The reason generic AI imagery never quite fits a fashion brand is that it was trained on everyone. A custom model is trained on you — and that difference is the whole point.
What it is
A visual model that learns your aesthetic.
You provide reference images — campaigns, lookbooks, product shots — and brand assets. We fine-tune a private model that internalises how your label looks: the drape of your fabric, the bodies you cast, the light you shoot in.
From then on, every module on the platform generates through your model. The same brief produces output that reads as yours, whether it's a PDP packshot or an editorial campaign frame.
How it's built
From references to a production model.
- 01
Curate references
Gather the images and brand assets that define your look. Quality of references shapes quality of the model.
- 02
Fine-tune privately
We train a private model on your aesthetic — in minutes, not weeks, with no exposure to other workspaces.
- 03
Deploy to your workspace
The model powers every module. Your team generates on-brand assets immediately, with consistent personas.
See it
Same garment. Your campaign.
A plain studio packshot goes in; an on-brand campaign image comes out — the same piece, recast in your light, your mood, your model.
Why it's a moat
Specifics you own, not an average anyone can copy.
- Private by default
- Your model and its weights stay scoped to your workspace. We do not train public models on your content without explicit opt-in.
- Consistent identity
- Casting, fit, fabric behaviour, and editorial mood carry across every shot — not a different look each time.
- Not reproducible
- Competitors using general tools get a generic average. Your signature can't be prompted out of a model that was never trained on it.
- Owned by you
- Output rights are assigned to your workspace to the extent permitted by law. Enterprise plans can negotiate model portability.