For years, buyers have been asking Robert Wensley to build something just for them. This week, he did: the official launch of LiftGPT for Buyers.
What LiftGPT for Buyers is: the same AI assistant Investorlift built for sellers, now tuned for how buyers actually work. It's connected directly to nationwide MLS data (updated weekly), tax and deed records, mortgage data, HOA and permit history, crime and school scores, listing history and photos, and years of Investorlift's own marketplace activity - not a generic chatbot layered over public scrapers, but a tool built on the data underwriting actually depends on.
What it can do:
Generate ARV as a range, not a single number, with the underlying comps visible, adjustable, and mapped
Estimate rehab costs by trade and by market using regional labor-cost data, and let you share the estimate directly with a contractor
Calculate your max allowable offer for a flip, with editable assumptions - cost of capital, points, holding period, closing costs
Run rental analysis - rent comps, cap rate, cash-on-cash return, DSCR - with adjustable vacancy and expense assumptions
Flag risk factors automatically: permit history (to infer scope of work), flood zone status, insurance considerations, and local market trends like price cuts, days on market, and sale-to-list ratio
Pull people and ownership data: owner of record, mortgage balance, skip tracing, and reverse lookup by phone or email
Model seller-financing and creative-finance scenarios, solving for a target rate or target cash flow
Remember your buying criteria - cost of capital, buy box, financing terms - once you set them, so every deal after that is measured against your numbers
Schedule recurring searches that scan new listings against your buy box and send a daily or weekly summary
This is opening in a limited early-access batch while the team collects feedback before a wider rollout - if you don't see availability yet, it's coming.