Predictive ML & MLOps

UAE Property Deal Finder

An intelligent property deal finder that scrapes real-estate listings from Bayut and PropertyFinder across all 7 UAE emirates, scores deals, and displays them on an interactive dashboard.

  • Web Scraping
  • Deal Scoring
  • Python Dash
  • PropTech

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Listings scored A+ to F to surface the hottest deals. Illustrative walkthrough.

7UAE emirates covered
2live sources (Bayut · PropertyFinder)
A+→Fdeal grades
$0API cost — direct scraping

What's inside

Features

Real-time scraping

Fetches live listings from Bayut and PropertyFinder across all 7 emirates — Dubai, Abu Dhabi, Sharjah, Ajman, Ras Al Khaimah, Fujairah and Umm Al Quwain — using curl_cffi with no paid APIs.

AI deal scoring

Every listing is scored 0–100 and graded A+ to F, so hot deals (score > 80) rise to the top instantly.

Smart filtering

Filter by emirate, listing type, property type, bedrooms, price range and data source — apply with Search and refine on the fly.

Live refresh

Refresh scrapes new listings, de-duplicates by source + ID, adds only what's new, and reloads the dashboard with updated data.

Export to CSV

Download any filtered set of listings for offline analysis in one click.

REST API

A FastAPI service exposes listings and scores to other tools, with auto-generated API docs.

What it does

An intelligent property deal finder that scrapes real-estate listings from Bayut and PropertyFinder across all 7 UAE emirates, scores deals, and displays them on an interactive dashboard.

Project status: In-house tool built by Software Stem. Listing collection and deal scoring are currently being updated.

Deal grades

  • A+ (90–100) — Excellent deal
  • A (80–89) — Great deal
  • B (70–79) — Good deal
  • C (60–69) — Average deal
  • D (50–59) — Below average
  • F (0–49) — Poor deal

How it works

  1. Step 1. Live listings are scraped from Bayut and PropertyFinder across all 7 emirates.
  2. Step 2. Each listing is scored 0–100 and graded A+ to F to flag the best value.
  3. Step 3. Filters by emirate, type, bedrooms, price and source narrow the view; Refresh merges in new listings, de-duplicated by source + ID.
  4. Step 4. Combined data is snapshotted to JSON, any filtered set exports to CSV, and a REST API exposes the same data to other tools.

Where it's used

  • Real-estate investors
  • Buyer agents and brokers
  • Investment screening
  • Rental matching

Tech stack

  • Python
  • Dash / Plotly
  • curl_cffi
  • FastAPI
  • Pandas

Build something like this

This project is part of our AI for real estate in the UAE, machine learning and MLOps services and AI Visibility audit for real estate brands. Tell us your use case and we will reply within one business day with a first step, a price and a date.

Architecture

How the pieces fit

  1. 01Bayut · PropertyFinderscrapers with curl_cffi, all 7 emirates
  2. 02De-duplicatemerge by source + listing ID
  3. 03Deal scoring0–100 → grades A+ to F
  4. 04Dash + APIdashboard · filters · CSV · REST
InputProcessingOutput

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