Fudosan Souba Research is a free tool to check used-condominium price trends across Japan. Instead of asking prices, it uses actual transaction prices published by Japan's government (MLIT), so you see the real market rate. Browse median price per sqm, yearly trends, and breakdowns by building age and layout for every municipality, plus ward-level rankings for Tokyo, Osaka, Nagoya and Fukuoka. No signup needed. Paid plans add LINE alerts for underpriced listings and AI property analysis.
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Maker
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Hi Product Hunt! 👋 I built Fudosan Souba Research because checking real estate prices in Japan usually means looking at asking prices — not what places actually sold for. This tool aggregates the government's official transaction-price data (MLIT), so anyone can see the real market rate for used condos: median price per sqm, yearly trends, breakdowns by building age and layout, plus ward-level rankings for Tokyo, Osaka, Nagoya and Fukuoka. It's free and needs no signup. I'd love your feedback!
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Finally a real estate tool that shows actual transaction prices instead of asking prices. The ward-level breakdown for Tokyo was exactly what I needed, and not having to sign up was a nice touch.
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Love that you pulled directly from MLIT transaction data instead of listing prices, that choice alone makes this feel honest in a space full of guesswork. The no-signup approach is also a nice touch for just browsing.
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Love that you skipped asking prices entirely and pulled straight from MLIT transaction data, that decision alone makes this feel way more trustworthy than the usual listing fluff.
Finally a real estate tool that shows actual transaction prices instead of asking prices. The ward-level breakdown for Tokyo was exactly what I needed, and not having to sign up was a nice touch.
Love that you pulled directly from MLIT transaction data instead of listing prices, that choice alone makes this feel honest in a space full of guesswork. The no-signup approach is also a nice touch for just browsing.
Love that you skipped asking prices entirely and pulled straight from MLIT transaction data, that decision alone makes this feel way more trustworthy than the usual listing fluff.