A Bubble.io platform that lets real estate clients upload large property datasets and receive automated pricing outputs, with Google Maps integration for geographic context.
Real Estate Data Pricing Platform
↓ Scroll
A Bubble.io platform that lets real estate clients upload large property datasets and receive automated pricing outputs, with Google Maps integration for geographic context.
↓ Scroll
● WHAT WE DID
Real estate pricing at scale is fundamentally a data problem. An individual agent can price a home using intuition and comparables. Accurately pricing dozens or hundreds of properties across a market requires processing large volumes of structured data that existing tools were not built to handle without technical teams or manual workarounds.
Area Corporation needed a platform that could ingest proprietary datasets and surface accurate pricing outputs for clients who did not have technical backgrounds. They came to Revex to build it on Bubble.io.
The Challenge
The core challenge was data intake. Real estate datasets are large, inconsistently formatted, and messy in ways that vary by source. Building a bulk upload pipeline that could accept diverse property data, parse it reliably, and feed it into a pricing model without requiring manual cleanup put significant demands on the data layer.
The platform also needed to present outputs geographically. A pricing number without spatial context is harder to act on. Integrating Google Maps to anchor each priced property to its actual location was a critical part of making results useful.
The Solution
Revex built the platform on Bubble.io with a structured bulk upload workflow at its core. Clients upload datasets through the platform, which parses incoming records, standardizes the data, and runs it through the pricing logic. Results are displayed with per-property outputs and map-overlaid visualizations showing each priced unit in geographic context.
User authentication gates access to client-specific datasets, keeping data scoped to the correct accounts. The architecture was built to handle large data volumes without degrading performance for non-technical users.
The core product is a bulk dataset upload and parsing pipeline that accepts large real estate data files and outputs automated property pricing. A Google Maps integration places each priced property on an interactive map, giving clients spatial context alongside the data.
User authentication and client-scoped data access ensure each client works within their own dataset. The pricing dashboard presents results at the property level with filtering and sorting for navigating large output sets.
— More Work
See more of our work building products for ambitious teams.