A broker sends over a one-liner for a single-family rental. The price looks right. The neighborhood sounds familiar. You want to know if it fits your buy box, but the only way to find out is to pull comps, check rents, verify the neighborhood, and run the numbers yourself. You already know how to screen a deal. That’s not the problem. The problem is that doing it properly takes 30 minutes per property, and you’re looking at five new opportunities this week. By the time you finish screening, the best ones are already under contract. That’s exactly what this task is built to fix. sourcing 10 min Buy Box Fit Check - Single-Family Resi Acquisitions Upload an offering memorandum or listing summary for a single-family residential rental property or portfolio and provide your investment criteria. The AI coworker extracts key deal details, runs location research, fills data gaps using available tools, and delivers a pass/fail screening against your buy box. Who It’s For SFR investors and acquisition teams who need to screen inbound deals against their buy box quickly and consistently. What You Get Back A structured pass/fail screening report with a criteria comparison table, data-backed rationale, and a link to the full location analysis. Why It Matters Every hour spent manually screening deals that don't fit is an hour not spent on the ones that do. Task Inputs Offering Memorandum Required Upload the OM, broker one-liner, or deal summary for the property being screened Property Profile & Configuration Required Target property characteristics such as bed/bath count, square footage, lot size, year built, construction type, condition, and HOA status Market(s) & Neighborhood Characteristics Required Target market and neighborhood traits such as location, school quality, demographics, crime levels, and proximity to demand drivers Rental Performance & Yield Required Target rent levels, yield thresholds, and rental demand indicators (e.g., achievable rent above $1,800/mo, gross yield above 7%, rent-to-value above 0.6%, low vacancy submarket, rent growth above 3% trailing 12 months) Investment Strategy & Pricing Required Target strategy, hold period, pricing, and renovation scope (e.g., buy-and-hold, 7-10 year hold, sub-$300K all-in, light cosmetic renovation under $25K, positive cash flow) Tools Used Deep Location Analysis RentCast Generate Demographics Report Real Estate Data from Precisely Research Assistant: Quick What This Task Does You upload an offering memorandum (or broker one-liner, or listing summary) for a single-family residential rental property and fill in your investment criteria across four categories: property profile, market and neighborhood characteristics, rental performance and yield, and investment strategy and pricing. The Real Estate Analyst (with Memory) takes it from there. It reads the OM, extracts every screening-relevant detail, runs a Deep Location Analysis on the property address, and then systematically checks whether each of your criteria passes or fails. If there are gaps in the OM (missing comps, no rent estimate, unclear neighborhood data), the AI fills them using RentCast, Precisely, a demographics report, or web research. Nothing gets marked “Pass” without data to back it up. The whole process takes roughly 10 minutes of your time. The AI does the rest. Who This Task Is For If you’re acquiring single-family rentals and screening multiple deals a week, you already know the bottleneck isn’t finding opportunities. It’s filtering them fast enough to act on the right ones. This task is built for: Independent SFR investors who receive broker one-liners and need a fast, consistent way to check fit before committing to deeper diligence Acquisition analysts at SFR portfolio operators who screen dozens of deals weekly and need a repeatable, data-backed process Buy-and-hold investors scaling a rental portfolio who want every screening decision tied to their specific buy box, not gut instinct Real estate teams with defined investment criteria who need junior team members or virtual assistants to screen deals without losing quality or consistency In short: if you already have a buy box and a stack of OMs, this task gives you a screening decision for each one in minutes. Why It Matters The best SFR investors don’t win by finding deals nobody else sees. They win by screening faster and more consistently than everyone else. When a deal hits your inbox, the clock starts. The question isn’t whether you can evaluate it; it’s whether you can evaluate it fast enough to move first. You already know this. You’ve built your buy box. You know the rent thresholds, the neighborhoods, the price points. The criteria aren’t the problem. The problem is bandwidth. Pulling the comps, checking the rent data, verifying the neighborhood demographics, running the yield math: that’s 30 minutes per deal if you do it