The problem Estate Edge solves

The unique selling proposition of Estate Edge lies in its ability to forecast the future development and growth of different areas. By analyzing a decade's worth of satellite imagery and employing cutting-edge image classification models, Estate Edge detects developmental changes in geographical areas that signal potential increases in real estate value. This predictive capability empowers users to identify emerging hotspots for investment—areas that are expected to appreciate in value over time, due to factors such as industrialization, infrastructure development, or increased demand.

Estate Edge bridges the gap between satisfying immediate property needs and securing long-term investment gains. For homebuyers, this means finding a dream home that not only meets their current lifestyle requirements but is also a wise financial investment. For investors, it translates into identifying properties with the highest potential for capital growth, based on predictive insights into urban development and market trends.

As the real estate market continues to evolve, tools like Estate Edge will become increasingly indispensable for anyone looking to navigate the complexities of property investment with confidence. By democratizing access to advanced predictive analysis, Estate Edge is set to redefine the landscape of real estate investment, making it more accessible, informed, and strategic than ever before.

Challenges we ran into

Developing EstateEdge was a journey marked by significant challenges and obstacles that tested our team's resilience, innovation, and determination. Initially, our biggest hurdle was ideation. We knew we wanted to create something transformative in the real estate investment space, but finding an idea that was both innovative and feasible proved to be daunting. Countless brainstorming sessions later, we landed on the concept of leveraging satellite imagery and advanced NLP technology to predict real estate trends. However, this breakthrough was only the beginning of our challenges.

The next major obstacle was sourcing the data necessary to bring EstateEdge to life. Our application required not just current satellite imagery, but also access to a decade's worth of historical data. This requirement significantly narrowed our options, as many APIs offered only recent images or lacked the historical depth we needed. The quality of the satellite data was another critical factor. For our image classification models to accurately detect developmental changes, the images had to be clear and taken at similar times of the year to avoid discrepancies caused by seasonal changes, such as foliage or snow.