I’m putting together a machine-learning driven web app and need an experienced hand across the whole stack: Supabase for the database layer, FastAPI powering the backend, Vercel handling the build and edge deployment, with the domain and any auxiliary services running through Hostinger. The core goal is simple: ship a production-ready web application where the ML logic is exposed through FastAPI endpoints, persisted in Supabase, and served to users via a responsive front end that Vercel can build and deploy automatically on every push. I already have accounts on all four platforms and can grant access immediately. Here’s what success looks like for me: • Supabase: a well-structured Postgres schema, relevant RLS policies, and JWT-based authentication tied into the FastAPI layer. • FastAPI: clean, documented endpoints that wrap my existing ML models (PyTorch), complete with Pydantic validation and async support. • Vercel: CI/CD pipeline configured so each commit triggers tests, builds, and zero-downtime deploys. Environment variables and edge functions wired up correctly. • Hostinger: domain pointed to Vercel, SSL active, and any necessary DNS records or redirects in place. I’ll share the current code repo and a brief API contract once we start. Please keep changelogs clear and comment code where non-obvious decisions are made.