Guadalajara's urban tree census lists more than 1,300 species. When it's time to plant, almost no...Guadalajara's urban tree census lists more than 1,300 species. When it's time to plant, almost no...
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Alan Martinez
• 13h
Guadalajara's urban tree census lists more than 1,300 species. When it's time to plant, almost nobody opens it. The street just repeats whatever is already on the street.
Arabor turns that census into a decision you can defend. You enter the real constraints of the site, and the engine does three things in order: it eliminates what physically doesn't fit — mature height against overhead cabling, canopy against sidewalk width, water demand against available irrigation — then scores what survives across seven weighted criteria, then explains why each species landed where it did.
The weights shift with the site, not with the preference of whoever is filling the form. A narrow sidewalk weights root behavior at 25%. A park weights native origin at 25%.
And every result carries its own warnings: aggressive roots, problematic fruit in public space, allergenic potential, maintenance above budget. They're stated, not buried. A recommendation with no downsides attached is a recommendation nobody should trust.
Co-founded and built with a partner in Guadalajara. The real product runs on Next.js, React and TypeScript over a local SQLite catalog, and works fully offline — the engine is deterministic and calls no AI at all.
The link below is a standalone recreation of the recommender view, with the same scoring engine ported to JavaScript. There's an ES/EN toggle in the corner. Try setting irrigation to rainfall only and watch Ficus, Eucalyptus and Ahuehuete drop out before scoring even begins. https://claude.ai/code/artifact/a1d90ffe-37c5-4fe8-9915-9871f85c0795?via=auto_preview
AI DevelopmentData VisualizationProduct DesignLeafletNext.jsTypeScript
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