- Status
- Early access
- Type
- Generative UI runtime
Adaptive interfaces within defined rules.
Weft is a runtime where a model assembles each screen from a closed catalogue of components you define. Every screen is checked against a schema before it reaches a device, and every screen served is recorded so it can be reproduced. A surface can be pinned back to a hand-authored fallback. It is in early access and is not yet generally available.
- 08:02Contextrole + workload bucketed
- 08:02Composescreen assembled from catalogue
- 08:02Gateschema + lint passed
- 08:02Serve12ms from fingerprint cache
Same context, same screen. Every time.
Who should enquire.
Product teams that want screens to adapt to context without letting a model invent layout, styling or behaviour.
Limits.
- 01
Early access: scope, availability and support are agreed per team.
- 02
The model can only choose from the catalogue you define. It does not remove the need to design and test the components themselves.
- 03
The checks run on the structure of a screen. They do not judge whether the result is the best one for a user.
Questions about Weft.
What is Weft and who is it for?
Weft is a runtime for product teams in which a model arranges each screen from a closed catalogue of the team's own components and design tokens. It is for teams that want interfaces to adapt to context without the model inventing layout, styling or behaviour. It is in early access and not yet generally available.
How does Weft keep AI-composed screens within the rules?
By design, the model can only choose from a catalogue of components with typed properties. Each composed screen is checked against a schema and semantic rules before it is shown, every screen served is recorded so it can be reproduced, and a surface can be pinned back to a hand-authored fallback. The checks apply to a screen's structure. They do not judge whether it is the best screen for a user, and they do not replace testing the components themselves.
Request early access.
Early access: scope, availability and support are agreed per team.