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Daniel Fragoso

Field Repair Assistant

Installable mobile web app that guides an appliance technician through a repair: guided photos, AI reading of the rating plate, a branching step-by-step plan, evidence review, quote and customer report.

Architecture

Next.js App Router with PostgreSQL and Drizzle. Vision models extract model and serial data from photos as Zod-validated structured outputs, and the technician confirms before anything is planned; reviewing evidence can re-plan the rest of the job. Photos upload to S3 through presigned URLs, and an IndexedDB outbox holds work captured without signal. Runs in Docker on EC2 behind CloudFront; the origin only accepts CloudFront traffic carrying a secret header, and secrets live in SSM Parameter Store.

Highlights

  • Live in production
  • Offline-first photo capture and sync
  • Human confirmation before every AI step
  • Tiered model escalation with timeouts under the CDN limit
  • Classifier evals and a zero-cost mock mode