For investors who receive a lot of OMs

Every OM you receive.Broken down in a minute.

Upload the OMs that hit your inbox. ScoreOM pulls the numbers, rebuilds the NOI and scores each deal with the same criteria and models, so your whole pipeline sits in one normalized view you can rank and share.

Try it now. Drop in an OM, no signup needed.

Upload OM, flyer, deal summary or broker package

PDF, Word, Excel, or CSV · Max 50MB

~60s
OM to first pass
40+
fields extracted
100
point deal score
1
link to share it
What you get on every OM

From PDF to a clear first pass.

Real screens and recordings from the app. Every deal gets the same breakdown, so the tenth OM is as easy to read as the first.

Deal Score

See under the hood in a minute

Drop in the OM and get the numbers you check first, a plain-English brief and a 100-point score built on your criteria.

  • Going-in cap, DSCR, price vs. replacement, base IRR
  • Strengths and concerns pulled from the OM
✓Key strength
Fully leased

100% occupancy across 12 units.

From the OM
↗Opportunity
Below-market rents

Average rent per SF sits under market. Room to push on renewal.

Upside
!Concern
Tenant concentration

Hobby Knights holds 21% of GLA. A few tenants carry the rent.

Verify leases
Financials + Rent Roll

Find the real NOI

The operating statement is rebuilt with vacancy and reserves applied, next to a tenant-level rent roll with every expiration.

  • OM-stated vs. adjusted NOI, side by side
  • Near-term rollover and concentration flagged
↗NOI gap
-16% vs. the OM

Rebuilt with vacancy, expenses and reserves applied.

Adjusted
iTransparent
Estimates labeled

Reserves at $0.25/SF are flagged and editable.

!Rollover
2 leases end in 2025

Plaza Barber Shop and KK Sew & Vac.

Near-term
Offer Scenarios

Know your number before you call the broker

Returns at the ask and from 15% under to 5% over, plus bull, base and bear cases with the assumptions spelled out.

  • Green clears your target IRR
  • Same assumptions on every deal, so they compare cleanly
✓Your number
About 5% under ask

$2.40M returns 16.5%, clearing the 15% target.

Clears target
↗At ask
14.8% levered IRR

Just under target at $2.53M.

!Bear case
9.3% if the market turns

Flat rents and a 75bps wider exit cap.

DealBoards

Line up every deal you are looking at

Every OM you receive lands on a DealBoard, broken down the same way and ranked by score, price, cap rate, NOI and occupancy.

  • One normalized view of your whole pipeline
  • Boards by market, asset class, client or strategy
↗Normalized
17 OMs, one view

Every deal broken down the same way.

Same criteria
↗Sort any way
Score, price, cap, NOI

Ranked side by side, export to CSV.

Share

Share a DealBoard with one link

Send partners, lenders or clients a live board of deals on a map. They click the link and see the numbers. No login needed.

  • Map view of every deal on the board
  • Read-only deal pages with photos and key metrics
↗No login needed
Opens in any browser

Partners, lenders and clients just click the link.

Read-only
✓Live map
Every deal pinned

Click a pin for photos, score and key metrics.

Email + Files

Send the breakdown, files included

The moment you upload an OM, ScoreOM builds an Excel workbook and a Word brief. Email the whole deal breakdown in two clicks with both attached.

  • Excel workbook and Word brief generated on upload
  • Formatted deal page emailed to anyone
iBuilt on upload
Workbook + brief, automatic

An Excel workbook and a Word summary for every OM.

No extra steps
↗Two clicks
Email the full breakdown

Formatted deal page plus both files, to anyone.

Multiple documents

Feed it more, get a sharper read

Add the OM, rent roll, T-12, lease abstracts or a flyer to the same deal. A light OM with no rent roll or financials says little. The more you give it, the better the breakdown.

  • Several files per deal, re-analyze anytime
  • Tells you which documents would improve the analysis
Might improve analysisAdd the rent roll and T-12
Why not just use ChatGPT or Claude?

Same criteria. Same models.
Every OM.

A general AI chat like ChatGPT or Claude gives you a new take every time you ask. ScoreOM is repeatable: every OM runs through the same criteria and CRE models, so your view of the market is normalized and the scores actually compare.

Offering memorandums in different formats pass through one ScoreOM lens and come out as identical, comparable deal cards
73Buy
66Neutral
58Neutral
81Strong buy
45Pass
Every OMA different broker, format and story
One lensSame criteria, models and layout on every deal
ScoreOMGeneral AI chat
CriteriaYour criteria, applied the same way to every OMDepends on how you word the prompt that day
ModelsStandard CRE models: NOI rebuild, DSCR, IRR ranges, offer gridMath improvised per chat, hard to check
OutputThe same 40+ fields and layout on every dealA different paragraph every time
Scoring100-point score you can sort, rank and compareOpinions, no consistent score
RepeatableRun it again and get the same answerAsk twice, get two answers
Your pipelineDealBoards, map view and one-link sharingLost in a chat history

ScoreOM is a fast, consistent first pass for screening. It is a starting point for your underwriting, not a replacement for it.

Examples - rank on-market deals.

Upload an OM, see the numbers and the rent roll in under a minute.

EXAMPLE DEALSThese are sample outputs - your real OMs get the same analysis.
Not live deals
From OM to first pass
in 60 seconds
AI extraction
Quick return ranges
Instant scoring
Shareable deal view
Who it's for

Built for everyone who reads an OM.

Screen a stack of OMs before lunch.

Put every inbound deal through the same lens, then spend your time on the few that pencil.

  • A score and first-pass brief on every OM, in about a minute each
  • Rough return ranges and pricing context before the first call
  • Rank the whole pipeline on a DealBoard
↗Pipeline
Ranked by score

The best deal rises to the top.

↗Before lunch
About a minute per OM

Screen the stack, keep the few that pencil.

Share a DealBoard

One link. Your deals on a map. No login needed.

Curate a board for a partner, lender or client and send it as a single link. They open it and see every deal on a map with the key numbers, and can click into the full breakdown. No account, no password.

  • Name the board for your audience and add your contact info
  • White label it and keep the source OMs private
  • Set an expiration and see how many times it has been viewed
scoreom / shared dealboard
Asset-specific models

A dedicated model for the top three asset classes.

A grocery-anchored center doesn't score the same way as a warehouse or a suburban office building. Each asset type gets its own purpose-built model - so the signal you get is the signal that matters.

Retail
Model
Shopping centers, grocery-anchored, single-tenant NNN, QSR, mixed-use.
Tenant rosterRolloverAnchor credit
Industrial
Model
Warehouse, distribution, flex, last-mile logistics.
Clear heightDock doorsTenant credit
Office
Model
Multi-tenant office, medical office, suburban & urban CBD.
WALTTenant creditTI/LC load
We auto-detect the asset type from your OM and route it to the right model. No extra clicks.
Watch the walkthrough

ScoreOM in 80 seconds.

Who it is for, what it does with the OMs you receive, and how the scores, DealBoards and sharing fit together.

FAQ

Questions investors actually ask

Everything you need to know about using ScoreOM for pre-diligence.

Getting Started
Free Access
The Product
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