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Development of a Scalable Real Estate Bidding Platform with Advanced Search and Auction Features

leobit.com

Real estate

Financial services

Challenges in Real Estate Transaction Efficiency

Manual workflows, limited property visibility, and lack of real-time bidding capabilities hinder efficient property transactions. Existing solutions fail to connect buyers with unlisted properties or provide dynamic pricing insights.

About the Client

A proptech-focused holding company providing consulting and transaction support to real estate agents and property buyers

Goals for the Real Estate Bidding Platform

Develop a scalable MVP to attract short-term investment
Implement real-time bidding and auction notification systems
Enable property owners to list assets with automated data enrichment
Integrate geographic and historical pricing data for informed bidding

Core System Functionalities

Property listing with automated MLS data synchronization
Real-time bidding with SignalR notifications
Dynamic auction time controls and buyout options
Google Maps integration for location-based property search
Contract emulation workflow for transaction finalization

Technology Stack Requirements

.NET for backend development

Angular for frontend interface

SQL Server as primary database

Azure cloud deployment

Microservices architecture

External System Integrations

MLS (Multiple Listing Services) database
Google Maps API
Attom Data Platform for historical records
Slipservices API for unlisted property data

System Quality Attributes

Horizontal scalability for future feature expansion
Real-time data synchronization across services
Enterprise-grade security for financial transactions
High availability with 99.9% uptime SLA

Expected Business Outcomes

A 6-month MVP delivery timeline enabling immediate investor demonstrations, with potential to streamline property transactions through automated bidding, enhanced market visibility, and data-driven pricing strategies that align with modern real estate trends.