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Generative UI/UX Automation Engine for Rapid Screen Prototyping

Generative UI/UX Automation Engine for Rapid Screen Prototyping

A mid-sized SaaS product company based in Austin, Texas struggled to keep pace with rapid feature updates requested by enterprise clients. Their product and design teams spent hours manually building wireframes, user flows, and pixel-ready screens before development could begin. To accelerate delivery cycles, the organization partnered with an AI engineering team to build a generative UI/UX automation engine that could convert written ideas into structured wireframes and editable layouts instantly.

Image representing case study

52%

Improvement in sprint design velocity

5X

Faster generation of UI variations

40%

Reduction in designer workload

About  

Problem Statement

  • Designers required 2–4 days to create complete wireframes for new modules.
  • Iterations between product managers and designers caused bottlenecks.
  • No automated workflow existed to convert requirements into layout structures.
  • Scaling multiple design variations for enterprise clients was time-consuming.
  • Developers needed early visibility, but design delays slowed sprints.

Industry: SaaS

Services: Generative AI Development, Design Automation

Region: United States

Our Tech Stack

Tech stack we used

Solution Approach

  • Mapped the client’s component library and UI patterns into a structured design ontology.
  • Built a generative UI engine using GPT-4 Vision (UI-Structure Mode) to interpret feature descriptions and produce wireframe blueprints.
  • Created a Figma Plugin that injected generated screens directly into the design workspace as editable frames.
  • Indexed reusable components using Elasticsearch, enabling the model to assemble layouts based on prior designs.
  • Utilized AWS Lambda to ensure instant, scalable screen generation with minimal infrastructure overhead.
  • Added a rapid-preview dashboard for product managers to validate flows before design refinement.
  • Integrated caching with Redis to support iterative variations and reduce re-generation latency.

Benefits

  • Improved design team velocity by 52%, accelerating delivery of new features.
  • Enabled instant screen generation from simple textual prompts.
  • Reduced back-and-forth iterations between design and product teams.
  • Developers received early visibility into UI flows, improving sprint readiness.
  • Enabled scalable creation of multiple UI variations for client demos.

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