You know the moment. You have a clean deal, a quick back of the envelope rent, and a nagging doubt about whether you are light or optimistic. Pulling comps, adjusting for beds, baths, condition, and recency, then checking current listings eats time you do not have. Most teams either rush it or push it off. Both cost you. This task compresses the work into a single run and gives you a documented rent you can defend in underwriting or pricing. Underwriting ~5 min to run Analyze SFR Rental Comps Vic prompt Use Vic to run a rental comp analysis on the single-family home at 145 Oak Lane, including adjusted comps and zip rent trends. Purpose A human analyst needs about 45 minutes for the same work. The output supports faster rent decisions and underwriting with documented comp adjustments. Inputs Address Required Property Details Optional Output Format Optional Outputs A concluded achievable rent with point, range, and confidence level, plus an adjusted rental comp grid and zip market statistics. An Excel workbook and interactive map are available on request. Time saved Turns about 45 minutes into about 5 minutes. How it works Give Vic the property address and any details you have. Beds, baths, square footage, condition, and notes that affect comparability help, but the address alone is enough to start. If you want a specific format, say so. Otherwise the results come back in chat, and you can request an Excel comp grid and a map. Run it with: Use Vic to run a rental comp analysis on the single-family home at 145 Oak Lane, including adjusted comps and zip rent trends. Vic models the subject against selected rental comps and current active listings. It adjusts comps so you are not comparing a renovated three bed to a dated two bed as if they were the same. It then anchors the conclusion with zip level rent statistics and trends so you can see where your number sits relative to the local distribution. The output is direct. You get an achievable rent as a point, a range, and a confidence level. You also get the adjusted comp grid that shows what changed and why, plus zip market stats. If you ask for files, Vic provides an Excel workbook that mirrors the grid and a map so you can sanity check distance and clustering. This is not a black box estimate. The comp grid is the work. You can scan it in seconds, spot an outlier, and decide whether to keep or drop it. If your investment committee asks how you got to the number, you have the adjustments and the context on hand. The practical benefit is speed with traceability. A careful human pass takes about 45 minutes. This run returns in about five minutes, and the structure is consistent across deals. That consistency matters when you are comparing multiple acquisitions in a short window or setting rents across a portfolio. It also reduces the quiet drift that happens when everyone uses a slightly different comp set or adjustment logic. With a standard output that includes a confidence level and zip trends, your team can argue about inputs and comps instead of formatting and guesswork. Use it early in screening to avoid chasing thin deals, and again before you finalize underwriting or set a lease rate. The result is a rent you can defend, with the comps and context attached.