InvestorVI

A wholesaler, flipper, or rental investor evaluating a property had to pull comps manually, build a repair estimate, model ARV and cash flow in a spreadsheet, and separately track the lead in whatever CRM they'd cobbled together, if they had one at all. Formulas broke on mobile, templates went stale, and none of it flagged risk or told the investor what they should actually offer. The tools that did underwrite well were built for institutions, not for someone analyzing three properties a week from their phone.

The ask was one platform that could take a property address and basic numbers and return an institutional-grade answer: what's this worth, what's the risk, and what should I offer, in under a minute.

InvestorVI takes a property address and a few inputs and runs a complete deal analysis for the relevant strategy, land, fix & flip, rental, short-term rental, or home purchase, then drops the result straight into a connected CRM pipeline. I built the system end to end: the deal-analysis engine, the comps and market-data integration layer, the AI insights and negotiation-script generator, and the CRM pipeline that deals flow into automatically.

Each analysis calculates maximum offer, projected profit, ROI, cap rate, and a deal score, backed by comparable sales and market trend data, then surfaces plain-language risk flags and a recommended strategy instead of a raw number dump. From there, a deal moves into the CRM as a tracked lead with stage, next-action reminders, and one-click seller outreach scripts.

A single property submission fans out into parallel checks, comps retrieval, repair/ARV estimation, rental and cash-flow modeling, and risk scoring, and reconciles them into one deal score and recommendation rather than separate disconnected outputs. Every number shown (max offer, profit, ROI) is generated from the same underlying inputs the investor entered, so the negotiation range and the CRM record never drift out of sync with each other.

Because outputs directly inform real money decisions, every AI insight is labeled as an estimate, not advice, and the platform is built to surface confidence and data recency rather than present a single number as certainty.

Deal analyses are versioned so an investor can see how a property's numbers shifted as new comps came in, and every CRM stage change and outreach script is logged against the deal's history rather than living in someone's texts. Payments run through Stripe, and the platform is designed mobile-first so an investor can analyze a deal standing in a driveway, not just at a desk.

Moving from ad hoc spreadsheets to one connected workspace changed how investors worked day to day: deal evaluation moved from a reactive, after-the-fact gut check to a same-minute decision made before an offer went out.