Commercial Real Estate Acquisition Intelligence

Now available: connect Deal Screen to compatible AI assistants

Screen commercial deals in minutes. Bid with confidence.

Upload a broker package or enter deal assumptions. Apply your buy box, calculate a maximum bid, stress-test the downside, and identify the risks that matter before full underwriting.

Connect your underwriting engine to compatible AI assistants—including workflows using Claude and ChatGPT—and automate repeatable acquisition work.

Multifamily · Mixed-use · Neighborhood retail · Small industrial

Screening Result

24-Unit Multifamily · Value-Add

Proceed w/ Conditions

Maximum Bid

$4.08M

Asking Price

$4.25M

Spread

-4.0%

DSCR (base / downside)1.31x / 1.18x
Debt Yield9.8%
Stabilized Cash-on-Cash9.4%
Operating expense ratio vs. benchmarkBelow range

Illustrative output. Figures are sample data, not an appraisal or valuation.

Works with your AI workflow

Your underwriting engine, inside the AI workflow you already use.

Kuma Deal Screen MCP product mark

Kuma Deal Screen MCP

Connect with compatible AI assistants

Claude logo

Claude

OpenAI logo

ChatGPT

Compatible MCP client icon placeholder

Other supported MCP clients

Bring controlled deal analysis into the assistant your team prefers — without rebuilding your buy box, spreadsheets, or underwriting rules in every workflow.

Claude is a trademark of Anthropic. ChatGPT is a trademark of OpenAI. Use of these names or logos does not imply affiliation with or endorsement by Anthropic or OpenAI.

Secure, authenticated access to approved underwriting tools. AI-client availability depends on your provider, plan, settings, and supported MCP integrations.

Kuma MCP for Deal Intelligence

Your underwriting engine—available inside your AI workflow.

Kuma MCP gives authorized AI assistants and internal agents secure access to your deal-screening, maximum-bid, scenario-analysis, and investment-memo tools.

Explore MCP Access
  1. Step 1AI assistant or internal agent
  2. Step 2Kuma MCP
  3. Step 3Your buy box and underwriting engine
  4. Step 4Decision-ready output

The problem

Most acquisition time is spent on deals that were never going to work.

The bottleneck is not judgment. It is the hours between receiving a package and knowing whether the asset clears your criteria at any price.

Inconsistent broker packages

Every OM, T-12, and rent roll arrives in a different format, with different line items and different definitions of net operating income.

Slow spreadsheet underwriting

Rebuilding a model for each deal costs hours before you know whether the asset can clear your return thresholds at any price.

Decisions on optimistic assumptions

Pro-forma rents, understated expenses, and unmodeled tax reassessments quietly push deals past your criteria.

How it works

Three steps to a decision — and an optional fourth for AI workflows.

01

Upload or enter the deal

Upload an OM, T-12, rent roll, and financing terms — or start with a few key assumptions.

02

Apply your buy box

Set the return targets, leverage limits, debt-coverage requirements, and risk thresholds that define a good deal for you.

03

Get a defensible decision

Receive a maximum bid, base and downside results, red flags, and a clear recommendation to proceed, investigate, or pass.

04Optional

Automate through MCP

Connect approved AI tools to run consistent underwriting workflows using the same controlled investment-policy logic.

Capabilities

A structured underwriting engine, not a chat window.

Every screen runs the same normalized inputs through the same explicit rules, so results are comparable across deals and across your team.

Deal Quick Screen

Enter key financial inputs or upload deal documents to produce an immediate acquisition screen.

  • Screen from documents or manual entry
  • Current and stabilized NOI side by side
  • Proceed, proceed with conditions, or pass

Buy-Box Decision Engine

Set the investment criteria that define a good deal, then apply them consistently to every package.

  • Markets, asset types, and size ranges
  • Max leverage, min DSCR, min debt yield
  • Cash-on-cash, hold period, exit cap

Maximum Bid Calculator

Calculate the highest purchase price that still satisfies your return and debt-coverage criteria.

  • Price solved from your thresholds
  • Binding-constraint identification
  • Spread against asking price

Downside Scenario Analysis

Stress-test the deal before it becomes a signed LOI.

  • Rent, expense, vacancy, and rate shocks
  • Exit-cap expansion sensitivity
  • Base, downside, and upside side by side

T-12 and Rent-Roll Normalization

Turn inconsistent broker financials into a clean underwriting input set.

  • Standard chart of accounts mapping
  • Rent roll reconciled to the T-12
  • Missing and unverified items flagged

Risk and Diligence Flags

Surface the concerns that change price or kill deals — early.

  • Rollover and tenant concentration
  • Expense and rent reasonableness checks
  • Diligence questions to send back

Investment Memo Export

Generate a decision-ready report your committee can read in five minutes.

  • Returns, assumptions, and scenarios
  • Recommended price and conditions
  • Branded, shareable export

MCP for Deal Intelligence

From deal screen to AI-powered acquisition workflow.

Give your team a secure way to call approved underwriting tools from AI assistants and internal workflows—without sacrificing your standards, assumptions, or audit trail.

  • Consistent underwriting across every deal
  • Controlled access to approved tools
  • Configurable investment-policy rules
  • Faster deal comparison and memo creation
  • Organization-level security and usage tracking
See MCP Capabilities

AI workflow · Kuma MCP

Prompt

Compare these two 24-unit multifamily opportunities and tell me which one meets our downside DSCR and cash-on-cash targets.

Tools called: compare_deals, analyze_downside_case

Underwriting result

Recommendation: Pursue Deal A

Maximum Bid
$4.08M
Base-Case DSCR
1.31x
Downside DSCR
1.24x
Stabilized Cash-on-Cash
9.4%

Key risk: Property-tax reassessment not modeled

Required next step: Verify T-12 utility expenses

Inside the analysis

The numbers your committee asks for, on every deal.

Deterministic calculations, visible assumptions, and the binding constraint identified — so a recommendation can be defended, not just delivered.

Current NOI

$284,600

T-12 normalized

Stabilized NOI

$338,200

Year 3

DSCR

1.31x

Min 1.25x

Debt Yield

9.8%

Min 9.0%

Equity Required

$1,146,000

Incl. closing + CapEx

Maximum Purchase Price

$4,080,000

Binding: DSCR

Five-Year IRR

14.2%

Target 13.0%

Cash-on-Cash

9.4%

Stabilized

Exit Cap Sensitivity

-$212k / 25 bps

Value impact

Sample figures shown for illustration only.

Why not a general AI tool

Purpose-built for commercial acquisitions.

Generic AI tools

  • Broad, general answers
  • Inconsistent assumptions between deals
  • No defined investment criteria
  • No maximum-bid logic
  • No documented underwriting policy

Kuma Deal Screen

  • Structured commercial underwriting
  • Configurable buy-box rules
  • Deterministic return and debt metrics
  • Base, downside, and upside scenarios
  • Clear diligence flags and decision-ready reports

Who it's for

Built for people who buy buildings.

Independent CRE Investors

Screen more packages per week without hiring an analyst or rebuilding a model each time.

Acquisition Teams

One investment policy, applied identically by every person sourcing deals.

Multifamily Buyers

Rent roll reconciliation, renovation premiums, and tax reassessment modeled up front.

Mixed-Use Investors

Blend residential and commercial income streams with separate assumptions and risks.

Neighborhood Retail Buyers

Rollover schedules, tenant concentration, and recovery assumptions made explicit.

Small Industrial Investors

Short-WALT exposure, market-rent gaps, and CapEx reserves tested against your thresholds.

Pricing

Plans that scale from one investor to a full acquisitions team.

MCP access begins with the MCP Access plan at $299/month. Save up to 20% annually.

Starter

Individual investors screening a limited number of deals.

$49/month

  • Manual deal entry
  • Core commercial deal quick screen
  • Base-case underwriting metrics
  • Maximum-bid calculation
  • Standard buy-box templates
Start Screening

Pro

Active investors who want faster underwriting from broker documents.

$149/month

  • Everything in Starter
  • Up to 50 analyses per month
  • T-12 upload and normalization
  • Rent-roll upload and normalization
  • Base, downside, and sensitivity scenarios
Start Pro Trial
Built for AI workflows

MCP Access

Active investors and operators who want to use Deal Screen inside approved AI workflows.

$299/month

  • Everything in Pro
  • Hosted MCP connection
  • Connect with compatible AI assistants
  • Guided connection setup for supported clients
  • Secure organization-level access
Get MCP Access

Team

Small acquisition teams that need collaboration, governance, and higher usage.

$749/month

  • Everything in MCP Access
  • Up to 5 users
  • Shared team workspace
  • Role-based permissions
  • Team-level buy-box policies
Start Team Plan

Enterprise

Larger investment firms, platforms, and companies that need tailored integrations.

Starting at Custom

  • Everything in Team
  • Custom AI workflow and agent integrations
  • Custom MCP tools and permissions
  • Custom user and usage limits
  • Custom underwriting-policy configuration
Talk to Sales

FAQ

Questions worth answering before you buy software.

What property types does Deal Screen support?

Multifamily, mixed-use, neighborhood retail, and small industrial assets are supported today. Other income-producing commercial property types can generally be screened using the flexible income and expense inputs, though the built-in benchmarks and flags are tuned to the four primary types.

Does this replace full underwriting?

No. Deal Screen is a screening and decision-support layer that sits in front of full underwriting. It tells you quickly whether a deal can meet your criteria and at what price, so your detailed model, site visit, and diligence effort go only to deals that deserve them.

Can I use my own return thresholds and buy-box rules?

Yes. Target markets, asset types, maximum leverage, minimum DSCR and debt yield, cash-on-cash and IRR targets, hold period, and exit-cap assumptions are all configurable. Rules are saved as your investment policy and applied consistently to every screen.

Can I upload T-12s, rent rolls, and offering memorandums?

Yes, on Pro and Team plans. Documents are parsed and mapped to a standard input set, unit-level rents are reconciled against the operating statement, and anything missing or unverified is flagged for your review before results are produced.

How does the downside analysis work?

You define the stress you care about — lower rents, higher expenses, longer lease-up, higher interest rates, additional CapEx, exit-cap expansion — and the same normalized inputs are re-run under those conditions. Base, downside, and upside results are shown together with the debt-coverage and return impact of each.

Is my deal information private?

Your deals, documents, and buy-box rules belong to your workspace and are not shared with other customers. Data is encrypted in transit and at rest, access is scoped to your users, and your deal content is not used to train third-party models.

Is this investment, lending, or appraisal advice?

No. Deal Screen is a decision-support and underwriting workflow tool. It does not provide investment, legal, tax, lending, or appraisal advice, and its outputs are not a valuation or an offer. All assumptions, results, and decisions remain yours.

Kuma Deal Screen is a decision-support and underwriting workflow tool. It does not provide investment, legal, tax, lending, or appraisal advice, and its outputs are not appraisals, valuations, or offers to buy or sell real property. All assumptions and decisions remain the responsibility of the user.

Know your maximum bid before you waste time underwriting.

Screen your next deal in minutes and put your underwriting hours where they earn a return.