Google’s Envisioning Studio is testing two fashion-specific Flow workflows with Jane Wade and Sergio Hudson for their SS27 show preparations. Wade’s tool focuses on styling and model-card visualization; Hudson’s models runway staging, lighting, spatial flow and budget parameters. Both are presented as planning aids in a beta collaboration—not as replacements for fittings, production crews or human creative decisions.
Google Flow is a creative studio for generating and editing images and video, with tools for organizing projects, prompting new work and refining outputs. The fashion workflows put that general idea into two very different production problems: deciding what a look should be before cutting fabric, and deciding how a runway should work before building the set.
Wade’s styling suite previews looks before production
Jane Wade’s workflow moves visual decisions earlier in the process. It can explore garment colorways and fabrics alongside accessories, eyewear, hair, makeup and layered garments. The outputs include full looks, headshots, detail views and dressing-card-style layouts that help a team compare possibilities before committing to a physical sample.
The suite also includes an automated model-card generator intended to simplify a workflow previously handled through Adobe Illustrator and produce print-ready cards. That matters for a small studio: a single visual reference can bring the garment, beauty direction and cast presentation into the same planning conversation.
Wade estimates that visualizing a look before cutting it could save about $1,000 at the factory. That figure is her estimate for a possible saving, not a guaranteed result. Her reported workflow still included physical fittings, with every look tried on a model before final decisions.
The broader Flow interface shown in the official tutorial includes a project grid, a Prompt Bar, localized Lasso editing, model selection and Camera Control. It provides context for the kind of iterative workspace behind the fashion use case, but it does not demonstrate Wade’s styling suite or Hudson’s runway tool.
Hudson’s tool previews runway staging and budgets
Sergio Hudson’s workflow tackles the space around the clothes. It can model venue dimensions, lighting, mood, prop placement, model movement and budget parameters before physical staging is built.
Hudson says the process allowed his team to run dozens of spatial iterations while keeping the financial limits of a show in view. In practical terms, the tool lets a team discard an impractical staging idea earlier, before it becomes a construction, lighting or venue commitment. The number of iterations is Hudson’s reported observation, not a standardized performance measurement.
| Workflow | Collaborator | Planning job | Variables explored | Practical output |
| Styling and model cards | Jane Wade | Preview looks before production decisions | Fabrics, colors, accessories, eyewear, hair, makeup and layered garments | Full looks, headshots, detail views and dressing-card-style layouts |
| Runway staging | Sergio Hudson | Preview the show environment before construction | Venue dimensions, lighting, mood, props, model movement and budget parameters | Staging concepts and spatial iterations to support production decisions |
Where visualization stops
The most important boundary is physical validation. Wade’s process still used fittings, and her final-image approach retained real people, a real studio, a photographer and a stylist. The AI workflow helps compare possibilities; it does not turn a generated preview into a finished garment or campaign image.
The same applies to the runway tool. It can help a team reason about layout, lighting and cost before construction, but it does not replace pattern-making, materials, labor, models or the people responsible for the show’s creative direction.
