Building LOIHub: An Intelligent Platform for High-Stakes Real Estate Transactions

LOIHub's vision was to disrupt the high-stakes commercial real estate market by automating the tedious and error-prone review of Letters of Intent (LOIs). The manual process required a team of experts to sift through dense legal documents to extract and summarize critical data like terms, escrow conditions, and inspection contingencies. Their initial prototype was a proof-of-concept, but it was too slow (2 minutes per document) and inaccurate (~50%) for commercial use. They needed a partner to engineer a production-grade system with the data science expertise to build the core IP and the full-stack capability to create a secure, multi-user platform.

• Drastically improve performance: Reduce document processing time from minutes to seconds.
• Boost Extraction Accuracy: Increase the accuracy of key term extraction to an enterprise-ready level (85%+).
• Develop Core IP: Create a custom machine learning pipeline that could be continuously improved.
• Build a Collaborative Web Application: Design a secure, multi-user platform with a rich, role-based permission system for teams.
• Ensure Verifiability: All extracted data points had to be seamlessly linked back to their original source within the document for quick expert review.

Leading a 4-person team over the course of a year, Maximum Labs took end-to-end ownership of the project, from strategy to deployment on Azure. We began by re-architecting the data and machine learning strategy.

Our core innovation was a custom machine learning pipeline that not only automated the extraction and summarization of complex terms from LOIs but also featured a critical feedback loop. When an expert reviewer on the platform made a correction, that update was fed back into the ML pipeline, allowing the model to continuously learn and improve over time.

Animated GIF demonstrating POC of semi-final ML model document processing integration.

We engineered the system to seamlessly map every extracted entity back to its original source in the uploaded document, building deep user trust and enabling fast verification.

To bring this IP to life, our team built a sophisticated full-stack web application. A key feature was the rich, role-based permission system we designed, which allowed teams of users to oversee and apply discretionary access across any document within their shared workspace. This entire system was deployed to a secure, scalable Azure environment, turning LOIHub’s vision into a powerful, market-ready platform.

Screenshot of user management POC.

Working with our in-house designer, all of our internal POC's recieved full-design cycles with several rounds of feedback before fully implementing a polished product deployed in a containerized service on Azure.