Django property data platform

SEA APTS

A property aggregator that collects condos, apartments, homes and villas into one searchable Django platform.

Industry: Property and travel
Platform: Django / Python; evolved from Wix + Velo
Engagement: Studio-owned product and data platform

SEA APTS began as an internal Wix and Velo project designed to make rental research easier across several Thailand destinations. It has since been rebuilt as a Django-based platform, turning an earlier website experiment into a more capable data product.

01Current Django search interface with region, property type, budget, source and text filters.

02Live result cards bring cleaned listings from multiple sources into one browsable view.

03The earlier Wix and Velo version established the concept before the Django rebuild.

01 / THE SITUATION

What needed to change.

Property data arrives from multiple sources with different field names, incomplete details and duplicate listings. A useful aggregator must do more than collect pages: it needs a consistent data model and a repeatable quality process.

02 / THE WORK

What we were responsible for.

Seven custom Python bots collect listing data on a weekly schedule. The pipeline normalizes records, performs quality checks and removes duplicates before information reaches the public directory. Django provides the application, administration and search foundation.

03 / THE RESULT

What the new approach made possible.

The current platform provides one structured search experience across condos, apartments, homes and villas while preserving a traceable weekly data workflow behind it.

04 / KEY DECISIONS

The thinking behind the implementation.

Treat collection and publication as separate stages

Raw source data is processed before it becomes a public listing, keeping validation and presentation concerns distinct.

Normalize several property types

Condos, apartments, houses and villas share core fields but retain the details needed for useful comparison.

Keep weekly work repeatable

Seven bots, cleanup rules and duplicate checks turn a recurring research task into an operational pipeline.

Preserve the product’s real history

The case study shows the earlier Wix/Velo interface as part of the path to the present Django platform rather than rewriting that history.

DjangoPython7 collection botsWeekly processingCleaning and deduplicationProperty searchAdmin workflow

NEXT STEP

Need a related capability?

Bring the business problem, existing system and intended users. We will help identify the smallest sensible next step.

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