If it's personal, it clicks
BakerStreet Recommendation is the side of our portfolio that focuses on personality-led recommendations — finding the right thing for a specific person, not just the most popular thing for everyone. The signature app in this pillar is CarMatch, a four-minute survey that pairs you with cars across 39 brands and 1,200+ models in the 2026 U.S. catalog based on how you actually drive, what frustrates you, and what a great trip feels like.
Conventional recommendation tools start with specs and filters — "show me SUVs under $40K with AWD and 30+ mpg." That works if you already know what you want. Most people don't. They have a feeling — "something fun but practical, that handles weekends and doesn't feel like a tank in the city" — and they want help translating that feeling into a short list of cars worth driving. That's the gap CarMatch fills, and it's the lens we apply to every recommendation app in this pillar.
The CarMatch detail page below walks through what the app does, who it's for, how the matching algorithm weighs eight independent dimensions, and what makes the results different from Edmunds, KBB, or Cars.com. Future Recommendation apps from BakerStreet AI will share the same DNA: behavior-first, transparent scoring, original content, no sign-up gate.