Overview
A full-stack predictive analytics platform that turns raw data into ML-powered forecasts, delivered as a subscription SaaS. I built the entire stack: a Python and FastAPI backend serving the machine-learning models, a React and TypeScript dashboard for end users, secure JWT and OAuth2 authentication, and Stripe-powered billing.
The Challenge
The client needed to productise a machine-learning model into a real, paying SaaS — not just a notebook. That meant a secure API around the model, user accounts and authentication, subscription billing, and a clean dashboard that non-technical users could actually use. It had to be production-ready and safe to launch.
What I Built
A Python / FastAPI backend exposing the predictive model through a fast, typed REST API
A React / TypeScript dashboard for running predictions and visualising results
JWT and OAuth2 authentication for secure, multi-user access
Stripe integration for subscriptions and recurring billing
A production-ready architecture with clear separation between the ML service and the application layer
Tech Stack
Python, FastAPI, React, TypeScript, and Stripe, with JWT/OAuth2 authentication.
Outcome
The client went from a standalone machine-learning model to a fully working, monetised SaaS — with secure authentication, subscription billing, and a polished dashboard, all built and shipped as a single full-stack engagement.
0 likes · 21 views · Dec 22, 2025
Full-stack predictive analytics SaaS with a Python/FastAPI backend, React/TypeScript dashboard, JWT & OAuth2 auth, and Stripe billing.
