AI rendering

AI rendering creates an image from the predictions of a generative model trained on vast numbers of pictures, rather than by simulating the physics of light. The model can start from a text prompt alone, but in architecture it is mostly used to dress a sketch, a SketchUp screenshot or a clay render with materials, lighting and mood. Results arrive in seconds or minutes.

Where it helps

It shines at concept stage. Stone, timber and concrete versions of the same massing, different seasons, day and night variations: all of these can be produced in a single sitting. Control methods that read depth and edge information from the input keep the geometry largely intact. AI has also found its way into conventional rendering pipelines, in denoisers and image upscalers.

Its limits

A generative model has no sense of dimensions. It may change the number of windows, shift a mullion or put a staircase somewhere that makes no sense. Keeping several views of the same scene consistent is hard, and materials rarely match real products exactly. For images used in sales or approvals, a physically based render from an accurately measured model is still the safer path. Good output depends heavily on the prompt, and our architectural rendering prompt guide collects examples for exteriors and interiors.