Challenges & Solutions

Built by our partner company, through our agreement with Ommega.io we can source this same talent to build your platform. One major challenge was designing a system that could automatically extract and normalize data from diverse real estate listing sources. Listings differ widely in structure and formatting, and agents needed a process that required zero manual cleanup. The solution was a FastAPI-based scraping engine powered by BeautifulSoup and custom parser rules that identify, extract, and clean key listing information such as address, price, property type, and features in real time.

Another key challenge was creating an intuitive front-end experience for agents who are not technically inclined. The React-based interface was designed with a focus on simplicity and automation — users can paste a listing URL, review auto-fetched details, upload or reorder images, and instantly prepare marketing materials. The responsive UI and guided workflow reduce cognitive load while maintaining full editing control.

Marketing automation posed its own complexities. The system needed to generate ready-to-post content for social media and video reels with proper formatting and optimized captions. This was achieved through AI-assisted templates that dynamically assemble property data, images, and agent information into cohesive marketing assets. The generated output can be exported or scheduled directly for publishing, minimizing turnaround times from hours to minutes.

Scalability and reliability were also essential. Marlon’s backend was built on FastAPI with PostgreSQL for structured data and AWS S3 for media handling, allowing the system to manage thousands of concurrent listings and large image sets efficiently. Modular API endpoints make it easy to extend integrations with MLS providers, CRM systems, and third-party content platforms as the product grows.