A multifamily acquisitions firm evaluating hundreds of deals a year.
Pre/3 sources and underwrites multifamily acquisition opportunities at volume, reviewing hundreds of deal packages a year. Every deal arrives as a mix of PDFs and spreadsheets, and almost every broker sends them in a different format.
Manual data entry was capping underwriting throughput.
Each deal package had to be read by hand and re-entered into a standardized Purchase Template. Pulling figures from T12s, rent rolls, and offering memorandums ran 25 to 30 minutes per deal, and with roughly 100 brokers sending files in their own layouts, the work never got faster with volume. Throughput was limited by how fast analysts could type, not by how many deals were worth a look.
An AI underwriting agent built around Pre/3's own process.
Custom AI Studio built an AI underwriting agent that reads raw deal documents and returns an analysis-ready Purchase Template. Analysts upload OMs, T12s, and rent rolls through a web dashboard. The agent extracts the financials, maps expenses to Pre/3's 12-category logic, and exports to Excel with the template's formulas intact.
Anything the agent isn't sure about gets flagged instead of guessed, so a person confirms the edge cases before export. A memory layer records those corrections and learns each broker's formatting, so the system gets more accurate the more deals it sees. Every processed deal is stored in a proprietary database for later comparison and benchmarking.
Real estate underwriting automation that scales with deal flow.
Underwriting that took 25 to 30 minutes now takes 2 to 5, recovering roughly 104 analyst hours a year. Pre/3 can evaluate more opportunities without adding headcount, and accuracy keeps tightening as more broker formats accumulate in memory.