Stories of Transformation
Real businesses. Real challenges. Real results powered by technology.
OUR CASE STUDIES
Case Study 1
REstate
We worked with a mid-sized brokerage facing exactly this problem. Their Follow Up Boss account was in place but practically empty. Follow-ups were being missed, leads were going cold, and the broker had no reliable way to see what was happening across the team.
We built and deployed REstate AI, a LangGraph-powered automation agent that connects directly to Follow Up Boss. Agents simply send an SMS or voice memo to a designated number, just like they already communicate in their day-to-day workflow.
Case Study 2
Land Development
In land development, time is one of the most expensive variables in a project. Every month a development waits on approvals, increases carrying costs, delays construction timelines, and pushes revenue further out. In markets like Miami, where many zoning, planning, and entitlement decisions are tied to monthly review and hearing cycles, even a missed submission window can push a project back by an entire month or more.
We worked with a mid-sized land development firm in Miami that was struggling with a fragmented approvals and coordination process. Their projects required ongoing interaction with agencies such as Miami-Dade County and the City of Miami Building Department, along with zoning reviews, environmental assessments, permit tracking, site plan coordination, and inter-department communication.
Case Study 3
CRE Developer
We built an AI-powered Commercial Site Selection and Location Intelligence Platform for a fast-growing commercial real estate development firm in Nashville. The platform brings demographic, mobility, zoning, market, and commercial data into one place, helping acquisition teams discover, evaluate, and shortlist properties for retail, office, and mixed-use developments.
By streamlining early-stage property screening, the platform enables developers to identify high-potential opportunities in minutes instead of weeks. Teams can compare sites against project goals and focus their due diligence on the opportunities that matter most.
Case Study 4
CRE Underwriting
In commercial real estate, fast and accurate underwriting can make the difference between winning and losing a deal. We worked with a multi-tenant industrial investor whose underwriting process was highly manual, requiring extensive spreadsheet work, document review, financial modeling, and repeated assumption changes. We built an AI-powered underwriting platform that automates the workflow—from extracting data from offering memorandums and rent rolls to generating financial models and investor-ready reports.
The platform enables instant scenario comparisons across interest rates, rent growth, vacancy, hold periods, financing structures, and LP/GP waterfalls, reducing underwriting time from days or weeks to just 1–2 hours.
