Professional OMs
in Minutes, Not Days

You bring the property. We handle the writing, the data, and the design. Every claim is grounded in real market data. Every layout is tuned for an investor audience, built to match the quality of a professional deal team.

Factual QA

Every number cross-checked against source data before export.

150M+ Property Records

ATTOM coverage across virtually every US market for comps and property history.

Trained on 100+ Real OMs

Modeled on real deals from 30+ national and regional brokerages.

Live Rental Market Data

Submarket rent trends, vacancy rates, and rental stats pulled live from RentCast.

Investment Thesis

AI frames the narrative around what makes this a compelling acquisition.

Factual QA

Every number cross-checked against source data before export.

150M+ Property Records

ATTOM coverage across virtually every US market for comps and property history.

Trained on 100+ Real OMs

Modeled on real deals from 30+ national and regional brokerages.

Live Rental Market Data

Submarket rent trends, vacancy rates, and rental stats pulled live from RentCast.

Investment Thesis

AI frames the narrative around what makes this a compelling acquisition.

Factual QA

Every number cross-checked against source data before export.

150M+ Property Records

ATTOM coverage across virtually every US market for comps and property history.

Trained on 100+ Real OMs

Modeled on real deals from 30+ national and regional brokerages.

Live Rental Market Data

Submarket rent trends, vacancy rates, and rental stats pulled live from RentCast.

Investment Thesis

AI frames the narrative around what makes this a compelling acquisition.

Factual QA

Every number cross-checked against source data before export.

150M+ Property Records

ATTOM coverage across virtually every US market for comps and property history.

Trained on 100+ Real OMs

Modeled on real deals from 30+ national and regional brokerages.

Live Rental Market Data

Submarket rent trends, vacancy rates, and rental stats pulled live from RentCast.

Investment Thesis

AI frames the narrative around what makes this a compelling acquisition.

Market Overview

Vacancy rates, rent trends, and neighborhood context from verified sources.

Census Demographics

Population, income, and renter percentages for every US market.

Walk Score

Walkability, transit, and bike scores cited for every property address.

Google Places

Nearby employers, amenities, and transit nodes mapped and cited automatically.

Market Overview

Vacancy rates, rent trends, and neighborhood context from verified sources.

Census Demographics

Population, income, and renter percentages for every US market.

Walk Score

Walkability, transit, and bike scores cited for every property address.

Google Places

Nearby employers, amenities, and transit nodes mapped and cited automatically.

Market Overview

Vacancy rates, rent trends, and neighborhood context from verified sources.

Census Demographics

Population, income, and renter percentages for every US market.

Walk Score

Walkability, transit, and bike scores cited for every property address.

Google Places

Nearby employers, amenities, and transit nodes mapped and cited automatically.

Market Overview

Vacancy rates, rent trends, and neighborhood context from verified sources.

Census Demographics

Population, income, and renter percentages for every US market.

Walk Score

Walkability, transit, and bike scores cited for every property address.

Google Places

Nearby employers, amenities, and transit nodes mapped and cited automatically.

See the Output

How It Works

Drop the Address

From your address, we automatically pull rent comps, property records, sale comps, neighborhood demographics, Walk Score, and nearby employers. All the supporting data, without touching a browser.

Add Your Deal Context

Upload your rent roll and T12. Add photos. Then write broker notes covering your thesis, value-add story, and local market read. This is what shapes how the AI tells your deal's story.

A Team of AI Agents Gets to Work

Multiple agents read your data, plan the narrative structure, and write every section in parallel, modeled on 100+ real OMs from 30+ brokerages. A QA agent verifies every cited number against source data before the result reaches you.

Review, Edit, and Export

Preview your finished OM, make quick edits if needed, then download as a PDF or PowerPoint. Ready to send or customize further.

FAQ

No. ChatGPT can draft copy and even produce a rough layout, but there are three things it cannot do. First, it has no verified data. Every number it produces is a plausible guess unless you manually supply and cross-check it yourself. OfferMemo.ai pulls live rent comps, sale comps, demographics, and walk scores from real APIs, then runs a post-generation QA pass that verifies every figure against the source before anything ships. Second, it has no OM template. The formatting it produces is ad hoc. OfferMemo.ai outputs investor-grade PDFs and PowerPoints built on templates modeled after national brokerage OMs, with consistent layouts, section hierarchy, and typography across every deal. Third, there is no audit trail. If a number is wrong in a ChatGPT output you have no way to know until a buyer flags it. The QA layer here flags or removes any claim it cannot verify against source data.

Every factual claim runs through a post-generation QA pass that cross-references numbers, business names, and property features against the source data. Financial figures are verified to within 1% and demographic stats to within 5%. Claims that cannot be verified are flagged or removed rather than left in. Fabricated data in an OM is a liability, not a minor bug, and the system was built specifically around that.

Drop a sample of your writing in the broker notes field. That section is the primary narrative driver for the entire document, so the model adapts to your voice, your sentence rhythm, and the way you typically frame a deal. Brokers who include detailed notes with their own language consistently get output that reads like them, not like a chatbot. The more you put in, the more it sounds like you.

We offer a custom template build for early firms. We replicate your layout, fonts, colors, and visual language so every OM looks like it came from your shop, not a generic tool.

A template gives you boxes to fill in. You still write every word. OfferMemo.ai writes the actual narrative: investment thesis, market positioning, risk framing, all of it grounded in your real data and modeled on 100+ OMs from 30+ brokerages. A designer handles the layout but still needs someone to write the copy. We do both.

We pull from RentCast (rent comps and vacancy rates), ATTOM (property records and sale comps), Google Places (nearby employers and amenities), the U.S. Census Bureau (demographics), and Walk Score. Every number in the OM is traceable to a real source.

Excel or CSV. We automatically parse it regardless of how your columns are laid out. No reformatting required.

PDF and PowerPoint (.pptx).

You can make quick edits directly in the review preview before exporting. If you need deeper changes, export to PowerPoint and edit from there.

Photos are optional. If you skip them, the layout adapts accordingly. Adding property photos significantly improves the visual quality of the final document.

Multifamily and industrial. Office and retail are coming soon.

Your rent roll and property data are stored in Supabase (hosted PostgreSQL) with row-level security. We do not share or sell your data.

Professional OMs in Minutes, Not Days

See the quality for yourself.