- Feb 11, 2026
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I’ve been working on an AI tool that learns how a dealership buys stock and generates a daily shortlist of vehicles from across multiple auction platforms. The goal is to reduce the time spent trawling through listings and instead surface the small number of cars that are most likely to be good buys based on your past purchases and current market data.
It goes a bit beyond basic filters — it applies rules at a make/model level, looks at things like mileage vs age, condition, pricing vs market, and ranks everything into a daily “top picks” list.
Roughly how much time are you spending each day going through listings? Do you think it would realistically save you time, or would you still want to go through everything yourself?
More details on how it works here:
Vehicle Recommendation Engine | Boring Automation
It goes a bit beyond basic filters — it applies rules at a make/model level, looks at things like mileage vs age, condition, pricing vs market, and ranks everything into a daily “top picks” list.
Roughly how much time are you spending each day going through listings? Do you think it would realistically save you time, or would you still want to go through everything yourself?
More details on how it works here:
Vehicle Recommendation Engine | Boring Automation
