Future Garage

An AI platform that predicts which enthusiast and collector vehicles are likely to appreciate over the next 1–10 years. Input a specific car for a take, or browse curated cars-to-watch lists and market trend alerts.

Every five years, a previous-generation car becomes the obvious one to have bought. Most enthusiasts watch it happen instead of getting in. The pattern recognition behind which cars appreciate is real — production numbers, generational nostalgia, parts availability, the slow shift in what's collectible — but it's scattered across forums, auction archives, and parts catalogs that nobody indexes together.

Future Garage is the layer on top. Input a specific car — year, make, model, mileage, spec — and get a take on its 1-to-10-year appreciation outlook. Or browse the platform's curated cars-to-watch lists and market trend alerts as the data shifts.

The model pulls from auction sales, marketplace listings, supply trends, enthusiast and forum activity, social momentum, parts availability, production numbers, cultural nostalgia trends, and historical appreciation patterns. Not one signal — the convergence of all of them. Same way the most plugged-in collectors do it by feel, except at scale and across thousands of cars at once.

The proof set is cars where this would have been useful: Porsche 997 GT3s, Ferrari 458 Speciales, the Lexus LFA, manual V10 R8s, early AMG Black Series. Each one had a window where the case was clear before prices ran. The goal is being inside that window, on the right cars, in real time.

Audience starts as a public enthusiast tool — a place for younger collectors to think about cars before they're priced out. Could evolve into a subscription research platform for the operator side: dealers, brokers, serious collectors who want the data continuously instead of once.

Currently in early concept and research. Personal because I love cars — and because the kind of pattern-matching this requires is the kind of thing AI is genuinely good at, applied to a niche where the data is rich and the audience is hungry.