Case Study

Virtual Investor Pal

A real estate intelligence SaaS providing advanced investment analysis. It processes terabytes of property data to deliver financial insights, market trends, and rental estimations in real-time.

Virtual Investor Pal Architecture or Interface

Technology Stack

DjangoDRFPostgreSQL (10TB+)MongoDBRabbitMQDockerNextJSReactJsNoSQL

Not Given

The Approach

01
Architected the core backend using Django Rest Framework and PostgreSQL.
02
Engineered the asynchronous task queue using Celery and RabbitMQ for large payloads.
03
Designed all APIs for frontend consumption and external scraper integration.
04
Implemented the core business logic for financial calculations and market analysis.

The Result

Optimized query efficiency by 87% (200s to 24s) for complex property analysis.

Achieved sub-second (0.6s) data processing for high-volume JSON payloads.

Performed a high-integrity data migration on a 10TB+ PostgreSQL database.

Delivered a fully containerized (Docker) system for a portable, multi-server architecture.