REDATA | Commercial Real Estate Intelligence

Analyze deals from first look to investment committee.

REDATA is structured around the core questions investors ask before committing capital: what is the upside, what can break, and how does the opportunity compare to alternatives?

How REDATA works

REDATA turns the handful of numbers visible on any commercial listing into a full underwriting view — no spreadsheet wrangling required.

Enter or import the basics Asking price, square footage, year built, and asset type — or paste a LoopNet listing to import it in one step.
REDATA builds the model It estimates NOI, structures the debt, and projects exit value from your inputs and market assumptions.
Get a transparent score Every deal is scored across four weighted criteria so you can see exactly what's driving the number.
Stress-test and export Run sensitivity analysis on price, cap rate, and hold period, then export the results for committee review.

Deal Scoring

Combine return targets, lease risk, market liquidity, debt structure, and basis into one transparent score.

Underwriting Workspace

Centralize assumptions for revenue, expenses, capex, financing, exit pricing, and downside scenarios.

Market Intelligence

Prepare for future integrations across comps, rent trends, vacancy, demographic shifts, and supply pipelines.

About Ethan Feingold University of Florida · Finance & PPEL

emanfeingold@gmail.com LinkedIn

REDATA is built by Ethan Feingold, a University of Florida student studying Finance and PPEL (Philosophy, Politics, Economics & Law) with a strong interest in commercial real estate. He created REDATA to turn the handful of numbers visible on any listing into clear, defensible investment decisions.

Built for the major commercial asset classes.

Start with the property type, then adapt assumptions, risk flags, and return metrics to the deal.

Multifamily

Rent growth, concessions, renovation premiums.

Industrial

Tenant credit, clear height, logistics demand.

Office

Rollover exposure, TI costs, leasing velocity.

Retail

Sales trends, co-tenancy, trade area strength.

Medical Office

Healthcare tenancy, long leases, recession resistance.

Self-Storage

Operational income, demand drivers, market saturation.

Data Center

Power capacity, hyperscaler demand, infrastructure vintage.

Score a deal in under a minute.

Enter what's visible on any LoopNet listing — asking price, square footage, year built, and asset type. REDATA estimates NOI, structures the debt, projects exit value, and scores the deal across four weighted criteria.

Ctrl+A - Ctrl+C any LoopNet listing, then paste here

Asset type Asking price Square footage Year built Advertised NOI optional Advertised cap rate % optional Holding period years

Property address

Optional — enables live comp data

Street address City, state ZIP

Optional. Refines scoring for occupancy, lease structure, capital needs, and tenant risk.

Estimated by REDATA

Derived from your inputs and live treasury rates

Going-In Cap Rate —

→

Est. Exit Cap Rate — +0.35% expansion assumed

Return summary

Levered IRR — On equity after debt service

Exit Value —

Value Spread —

Loading live rates…

Debt & structure

DSCR —

Debt Yield —

Est. Loan Amount —

Est. Debt Service —

Property intelligence

NOI —

Exit NOI — Grown at 2.5% annually

Price per SF —

NOI per SF —

Basic calculations

Target cap rate %

Cash on Cash Return — Annual pre-tax cash flow / equity deployed

Monthly Profit After Debt — Monthly NOI minus monthly debt service

Cash Down — Based on asset-type LTV

Offer for Target Cap Rate — Enter target cap rate above

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AI Market Intelligence

Tenant · Location · Lease · Supply · Pricing · Debt · Thesis

Deal Score —

Enter assumptions to score the deal

Sensitivity analysis

How does this deal hold up as assumptions change?

Stress test

Asking Price	Cap Rate	IRR	DSCR	Score