Manual comping is the process every investor learns first: pull nearby sold properties, evaluate which are truly comparable, apply adjustments for differences, and arrive at an ARV. In disclosure states, public sources show real recorded sale prices directly. In non-disclosure states, that data lives behind an MLS connection, an agent relationship, or a platform built to pull from MLS-sourced data.
ChatARV isn't purely automated. It is an AI-powered comping tool that runs the entire process for you, done for you, not just faster. It also gives you manual tools if you want them: toggle comps on or off, add your own, adjust the math, pulling from a wider set of data providers than most manual searches reach on their own. The real question isn't automated versus manual. It's whether to do the manual part inside ChatARV or somewhere else.
What manual comping involves
You identify the subject property's characteristics, search for recent sales of similar properties nearby, evaluate each sale for comparability, apply dollar adjustments for differences in size and features, and arrive at an adjusted average as the ARV.
Careful manual comping by someone who knows a market well is reliable, but it takes real time. A thorough manual comp typically runs 20 to 30 minutes per property. Under a compressed timeline, shortcuts start to add up: fewer comps get evaluated, adjustments get estimated instead of calculated, and that error carries through into the MAO, BRRRR projections, and flip profit calculations built on top of it.
What ChatARV does
ChatARV runs that same process automatically, pulling from MLS-sourced transaction data across a wide set of providers, which makes it less likely to miss a sale than a manual search on a single site. Enter an address and it identifies the subject property, selects the most relevant comparable sales by proximity, recency, and condition, applies adjustments for square footage, bedroom and bathroom count, lot size, and condition, and produces an ARV range.
The automation doesn't replace manual review, it gives you a starting point for it. The comps selected and the adjustments applied are visible in the report. Toggle individual adjustments on or off, swap out a comp you disagree with, or add one manually, the same manual work you'd do on Zillow or PropStream, just starting from a wider data set and a defensible number instead of a blank search.
Full exit-strategy analysis runs on the same address: wholesale MAO, BRRRR projection, flip profit, buy-and-hold cash flow, creative finance structure. All 12 non-disclosure states are supported using MLS-sourced data.
Where they differ
There are narrow cases where an experienced local investor or agent brings something ChatARV can't fully replace, personal knowledge of an issue that isn't in any data set, a relationship-based read on a seller's situation, or a genuinely one-of-a-kind property with no real comparables anywhere. But these are rare.
For the things people usually assume require a human, reading subdivision boundaries, spotting outlier sales, judging the extent of a renovation, ChatARV's AI selection can handle it. If you need to do more research, ChatARV has tools for pulling comps manually as well..
The bigger practical difference is speed and data coverage. ChatARV pulls from more data providers than a single manual search reaches, and turns an address into an ARV in under a minute instead of 20 to 30.
Who should use which
For the large majority of deals, run the address in ChatARV and use the built-in manual tools, toggle comps, add your own, adjust anything the automation got wrong, rather than starting a manual search over on Zillow, PropStream, or waiting on an agent. When a deal needs more manual research, that happens inside ChatARV too, using the Manual Comps tool.