Vitaly Kuzenkov
Listing aggregation

Every new listing, once, in one place

Listings from many property sites merged into one clean feed and scored against the buyer's criteria.

25,000 listings a month in one feed, seen 2 days sooner

Every new listing, once, in one place: the main product screen
Product screens, redrawn with sample data

An investment team was following new listings across 6 property portals and agency sites, each with different fields and many copies of the same apartment. I built a collector that reads every source on a schedule, puts address, price, size and features into one format, and merges duplicates by matching addresses and comparing photos. Each listing is scored against the team's buying criteria, and the best new ones arrive in a morning email and on a shared board. Result: about 25,000 listings a month reduced to one clean feed, and the team saw new stock 2 days earlier than before.

Client
Property investment firm, United Arab Emirates
Role
Design and build
Stack
Python, Playwright, PostgreSQL with PostGIS, OpenAI embeddings for duplicate matching, Next.js
Every new listing, once, in one place: the poster

Product screens, redrawn with sample data

  • Every new listing, once, in one place: product screen 2 of 5
  • Every new listing, once, in one place: product screen 3 of 5
  • Every new listing, once, in one place: product screen 4 of 5
  • Every new listing, once, in one place: product screen 5 of 5
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