DiveDeepAI

Green Residential

DiveDeepAI developed Green Residential, a smart application that works on efficient search of property according to the user selected features e.g., number of rooms, days on market, area etc.

About Client

A stealth startup focused on leveraging Artificial Intelligence and Machine learning to help people search for the suitable property.

The Challenge

The team at diveDeepAI had to connect to the client for a more refined and clean data that the APIs e.g. ntrees API and sabor could accept took a lot of time and effort. Moreover, the data we got from the API was first saved in the database and then retrieved with the help of RabbitMQ to present to the user.

The Solution

The Project uses some existing APIs for the efficient and fast search of the most suitable property. Buyers can look at their desired property by selecting their suitable filters and when they find one, they can get information relating to pricing and taxes. Moreover, the application supports different filters to facilitate the user e.g., area, division, max price, min price max rooms and baths, min rooms and baths etc. The user can submit an offer and keep track of submitted, accepted and declined offers. Besides this, users can search for the properties related to rent, sold etc. to get an idea of rent and property value in the area.

The Impact

The application semi-automated real estate agents’ work resulting in less time and effort involved in search of a good property. The user can submit an offer and keep track of submitted, accepted and declined offers, this tracking helps people to minimize the risk of frauds.

HIGHLIGHTS

Project in Action

Data Completion

Template Creation

Docker Deployment

Maintenance (speed efficiency was implemented).