System 05

DentaSmile AI

Cosmetic-dentistry previews from a patient photo. Self-hosted image editing on GPU with async job orchestration built around ~110 s inference times.

3services, async GPU jobs
Hover a step for what it does

Text version: Upload → Queue → Inference → Poll → Preview

Problem

Clinics wanted to show patients a realistic preview of their result; inference takes far longer than a browser request.

What I built

A three-service SaaS: Next.js front end, FastAPI job API, and a self-hosted Qwen Image Edit worker on RunPod L40S GPUs, with queued jobs and polling.

Key engineering decisions

  • Self-hosted open-weight model to keep patient photos off third-party APIs.
  • Async queue plus polling instead of long-held requests that time out.
  • Three services so the GPU worker can scale independently.

Validation and QA

Live demo deployed; every job is tracked from upload to preview with status and timing.

Result

A live product that survives slow inference: patients upload, wait, and get a preview without the app breaking.