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Executive Summary

A small-sized real estate agency, sought to enhance client satisfaction and improve property sales by offering personalized property recommendations.

About Client

A small real estate agency specializing in residential and commercial sales. The client aimed to enhance customer satisfaction and property sales by addressing challenges like manual property matching, scattered data sources, and low engagement. They sought an AI-driven solution to deliver personalized property recommendations, streamline operations, and support scalable, data-driven growth.

Problem Statement

Manual Property Matching

  • Realtors spent excessive time manually curating property suggestions.

Disparate Data Sources

  • Property, client, and market data were scattered across multiple systems, making it difficult to derive insights.

Low Engagement

  • Clients often received generic property recommendations, leading to low conversion rates.

Solution Overview

We implemented a cloud-based AI recommendation system using Azure Data Factory for data ingestion and transformation, and Databricks for advanced AI/ML modeling. The system provided:

Centralized Data Pipelines

Automated data ingestion and transformation to unify disparate datasets.

AI-Powered Recommendations

Tailored property suggestions based on client preferences and market trends.

Seamless Integration

Integrated with the agency’s CRM for real-time recommendations.

Scalability

A cloud-native solution designed for future growth and enhanced analytics.

Key Components

#1. Data Ingestion & Transformation:

  • Used Azure Data Factory to create ETL pipelines for ingesting data from MLS, CRM, and third-party sources.
  • Performed data cleaning, validation, and transformation using ADF Mapping Data Flows to prepare structured datasets.

#2. Data Storage:

  • Stored transformed data in Delta Lake on Databricks for optimized access and scalability.

#3. AI/ML Model Development:

  • Developed a collaborative filtering model using Alternating Least Squares (ALS) in Databricks with MLlib for personalized property recommendations

#4. Model Deployment:

  • Deployed the trained model on Databricks and exposed it as a REST API for real-time recommendations.

#5. Monitoring & Iteration:

  • Monitored recommendation accuracy and client interactions to iteratively improve model performance.

Tech Stack & Tools

Azure Data Factory

  • For data ingestion and transformation

Databricks

  • For data storage, feature engineering, model development, and deployment.

Delta Lake

  • Scalable and optimized data storage within Databricks.

MLlib

  • Collaborative filtering and recommendation modeling.

REST APIs

  • For seamless integration with the website and CRM.

Team Composition

  • Project Manager: 1
  • Data Engineers: 1
  • Data Scientists: 1
  • Software Developer: 1

Clientele

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Testimonials

Our Slam Book

Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

Antoine de Bausset

CEO - BEESPOKE

France

They are great at what they do. Very easy to communicate with and they came through faster than I hoped. They delivered everything I wanted and more! I will certainly use them again!

Vivek Singh

MARKETING & SALES HEAD - VARMORA

Gujarat

I really liked their attention to detail and their sheer will to do the job at hand as good as possible beyond professional boundaries.

Nimesh Patel

DIRECTOR - COVERTEK CERAMICA

Gujarat

Excellent work, and on time with all goals. Communication was very easy, and knowledge of work was excellent. Will be working with them on upcoming projects. I highly recommend.

Craig Zappa

DIRECTOR - ENA PARAMUS

United States

"I would like to recommend their name to one and all. No doubt" their web app development services cater to all needs.

Neil Lockwood

CO-FOUNDER - ESR

Australia

Aglowid is doing a great job in the field of web app development. I am truly satisfied with their quality of service.

Daphne Christoforidou

CEO - ELEMENTIA

United States

Their team of experts jotted down every need of mine and turned them into a high performing web application within no time. Just superb!

Talk To Us

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Contact number

+91 8487981277

+1 770 796 0077

Email Address

[email protected]

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