AI image generator — a Gradio app for rapid concept visuals

Problem

Clients evaluating generative AI often want to see and touch a working tool before committing to a project — not a slide deck, not a demo video. We needed a small, honest reference build of what an AI image generation app looks like in production: prompt in, image out, deployed and shareable. Something we could show a prospect in a meeting and say “we can build this for your domain.”

Approach

We built a Gradio application wrapping a Stable Diffusion image generation pipeline. The app presents a clean, prompt-driven UI — a single text field and a generate button — with sane defaults for quality, image dimensions, and safety filters baked in so the tool just works without a configuration manual.

The application is fully containerised with Docker, so deployment is a single command on any machine with a GPU. No hand-holding, no environment wrangling. The same container runs locally for development and on cloud GPU instances for heavier workloads, giving us a repeatable pattern we can adapt across projects.

Result

A working, deployable AI image generator app that doubles as our reference implementation for client engagements. When a prospect asks “what does it actually take to turn a model into a product?”, we show them this — the full path from model selection through UI design, containerisation, and deployment, in a fraction of the effort it takes to build from scratch.

The same stack — Gradio for rapid UI, Docker for portability, a managed model pipeline under the hood — transfers directly to client work. Swap the model, adjust the interface, and the core pattern holds.

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