91match score
Listings ranked by fit to the buyer's needs.
What it does
A recommendation engine that matches buyers to properties by learning preferences and ranking listings by fit.
How it works
- Step 1. Buyer preferences and listing features are encoded.
- Step 2. A ranking model scores how well each listing fits.
- Step 3. The best matches are surfaced first.
- Step 4. Feedback refines future recommendations.
Where it's used
- Real-estate portals
- Buyer agents
- Investment screening
- Rental matching
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