Ninja emerged from a real need: simplifying the complex and often overwhelming process of finding a new home in the bustling city of New York. Born from the founders’ personal experiences in navigating multiple real estate websites, Ninja aims to centralize this process, creating a one-stop solution for home searches.
Understanding the intricacies of the real estate market in NYC, Cube10’s team focused on delivering a platform that not only aggregates data but also enhances the user experience through intuitive design and advanced search functionalities.
The tech stack for Ninja was carefully selected to handle the complexities of real estate data aggregation and search functionality. Python and Celery formed the backbone of the application, managing tasks and workflows efficiently. Redis was chosen for its high performance as a database and cache, ensuring quick data retrieval. A microservices architecture was implemented for scalability, with Scrapy for web crawling, Apache Airflow for orchestrating data workflows, and ElasticSearch for advanced search capabilities. PostgreSQL was used for database management, providing robust data storage solutions. Connectors to major real estate websites were a key component, enabling the platform to fetch, aggregate, and update listings from various sources.
Our deep dive into user experience revealed the need for a platform that was not just a data aggregator but a solution that addresses the nuances of searching for a home in NYC. We understood that users needed a tool that could filter through the noise and present them with options that matched their specific needs and preferences. This understanding led to the development of advanced search filters and algorithms that could handle complex queries while delivering accurate and relevant results.
The design of Ninja was a critical component of the project. We prioritized simplicity and clarity, ensuring that users could navigate the platform effortlessly. The main color, yellow, was used strategically to evoke a sense of warmth and welcome, while also guiding users through the interface without overwhelming them. We implemented a responsive design, making sure the platform was accessible and functional across various devices and screen sizes. Special attention was paid to the visual hierarchy, making sure key information like price, location, and size was immediately visible and accessible. Interactive elements such as filters, search bars, and map integrations were designed to be intuitive, aiding users in refining their searches. We also focused on the integration of data from multiple sources, ensuring the information was displayed in a coherent and user-friendly manner.
The development process was approached methodically, starting with an MVP to gauge market response. The initial phase involved setting up the project environment, defining the database schema, and establishing a Scrum team for agile development. The data aggregator infrastructure was a cornerstone, handling the ingestion and processing of data from various real estate platforms. We developed a user-friendly front-end with essential landing pages and a results page that offered an interactive and informative property viewing experience. Search and filter functionalities were fine-tuned to ensure users could navigate the listings with ease. The MVP focused on integrating connectors to three major real estate websites, enabling the platform to gather and display a comprehensive array of property listings. Throughout the development, we maintained a focus on scalability, performance, and user experience, ensuring that Ninja not only met but exceeded user expectations in the crowded real estate tech market. Through the development of Ninja, Cube10 has demonstrated its capacity to create a highly functional, user-friendly platform that addresses the specific challenges of the NYC real estate market, setting a new standard for online property searches. The development of Ninja is an ongoing journey, and we are excited to announce that this innovative platform will soon be available to the public, transforming the way New Yorkers search for their perfect home.