Real-estate Voice Flow & Automation

This project focused on developing an AI agent capable of understanding and responding in the Egyptian Arabic dialect. By leveraging advanced natural language processing (NLP) and deep learning, we created a robust AI system that handles the diverse and nuanced nature of Egyptian Arabic. This AI agent significantly enhances client interactions for real estate professionals, setting a new benchmark in the industry by providing seamless communication experiences.

🔴 The primary goal was to develop an AI capable of recognizing and accurately responding to the rich lexicon, varied pronunciation, and syntactic features of Egyptian Arabic in real-time conversations. The project aimed to address the communication challenges within the real estate industry by providing a tailored AI solution..

Problem Statement

🔴 Real estate professionals in Egypt face challenges in effectively communicating with clients due to the complex nature of the Egyptian Arabic dialect, which varies significantly across regions. The project sought to overcome these barriers, improving the quality and efficiency of client interactions.

Role and Responsibilities

🔴 I led the project as the AI Engineer, responsible for designing and developing the core NLP and deep learning models. My responsibilities included curating a comprehensive dataset of Egyptian colloquial speech, developing machine learning algorithms, and integrating AI with communication platforms.

🔴 I collaborated closely with linguists and real estate professionals to ensure the AI’s responses were culturally and contextually appropriate. Additionally, I worked alongside engineers specializing in Twilio’s communication APIs and Eleven Labs’ voice generation technology to ensure a seamless integration of AI-driven interactions.