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Real estate analytics & advisory

Listing data collected at scale, turned into price trends, comparables and an advisor that can answer a buyer's question with evidence.

This solution grew out of our own product work on property data in Pakistan, so it is the one we can speak about in the most detail. It combines large-scale listing collection, a search layer built on Elasticsearch, and an AI advisor that answers questions using only the listings behind it.

What this covers

  • Automated collection of listing and price data from public sources
  • Address hierarchy parsing, deduplication and normalisation
  • Search with autocomplete, filters and geographic drill-down
  • Price trend charts by city, sector, society and property type
  • Comparable property analysis for valuations and pitches
  • AI advisor that answers buyer questions from your own data

The data problem underneath

Property listings are messy: the same unit appears five times, addresses are written six ways, and prices are quoted per marla, per kanal and per square foot in the same feed. Most of the engineering here is normalisation — parsing the address hierarchy, matching duplicates and converting units — because none of the analysis is worth anything until that is right.

An advisor that shows its working

The advisory layer answers questions like which sector fits a given budget, or what similar units recently listed for, and returns the specific listings behind the answer. Where the data is thin — a small sample, or a single point in time rather than a real series — the answer says so. We would rather return a limitation than a confident number that cannot be defended.

The essentials

Best forProperty agencies, developers, marketplaces, valuers and investors
Timeline6 to 14 weeks depending on sources and coverage
StackPython, Scrapy, MySQL or PostgreSQL, Elasticsearch, LangChain, LlamaIndex
DeploymentYour cloud account or a managed VPS
NoteData collection is configured to respect each source's terms and robots directives

Included as standard

The details that decide whether it works.

Scale collection

Scrapy pipelines running on schedule with change monitoring.

Elasticsearch

Fast, typo-tolerant search over hundreds of thousands of listings.

KPI dashboards

Inventory, asking prices and time-on-market by area.

Comparables

Ranked similar properties with the basis for the match shown.

Agency portal

Branded search and lead capture for your own website.

Data exports

Clean datasets and an API for your analysts and partners.

Start here

Have a system in mind? Let's scope it together.

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