AI-native multifamily underwriting

Underwrite multifamily deals in minutes, not days.

No data entryNo implementationNo waiting on analysts

Simply email a flyer, OM, rent roll, T-12, or offering package — and receive institutional-grade underwriting with a fully editable Excel model attached.

Free to startNo credit card requiredGet started in 60 seconds
OOutlook
Inbox
Sent
Drafts
Barry Stern · JLL9:12 AM
New listing — 123 Main St
New listing — 123 Main St, Seattle WA
Barry Stern <barry@jll.com>to you
9:12 AM

Sharing a new value-add opportunity — 123 Main St, 208 units in Seattle. Flyer attached.

PDF
123MainSt_Flyer.pdf
1 page · 640 KB
Forward
To
SubjectFwd: 123 Main St, Seattle WA
Hi Sam — can you underwrite this one?
PDF 123MainSt_Flyer.pdf
Reply to Sam
Tosam@slung.ai
Lonovo
ThinkPod
1
A broker sends a listing
208 units · value-add · Seattle
2
Forward it to Sam
No app — just email sam@slung.ai
3
Sam underwrites it
Any format → institutional model
4
Model back in minutes
Excel attached, fully editable
5
Ask Sam anything
Increase the entry cap rate by 25 bps
What are my biggest risks?
Draft an investment memo

The data behind every decision

Built on Slung’s proprietary multifamily dataset.

15M+
Units of Rent Comps
23K+
Properties of Financial Data
50
States Covered
$50B+
Assets Analyzed

How it works

Underwriting becomes a step you already do.

No new app, no behavior to change. You forward a deal the way you already do — and the model comes back.

1

Forward the deal

A broker sends a listing, or you forward one you’re chasing, to sam@slung.ai — flyer, OM, rent roll, T-12, or full offering package.

2

Sam underwrites it

Sam extracts and normalizes the data from any format, pulls neutral market comps, and builds an institutional-grade model.

3

The model lands in your inbox

Minutes later: the returns in the email body and a fully editable Excel model attached. Reply to adjust any assumption.

Modern multifamily apartment building
Brick multifamily apartment building

Start with whatever you have

No rent roll? No problem.

You don’t need the full package to get going. Sam underwrites from whatever you forward and sharpens as more arrives.

~90%

From just a flyer

Forward a one-page broker flyer and get a complete, decision-ready model back — no rent roll, T-12, or OM required to start.

~99%

With the full document set

Send the OM, rent roll, and T-12 and the model tightens to institutional precision — automatically, in the same thread.

Why Slung

Underwriting that meets you where you work.

Incumbents pull you into another app. Slung lives in the inbox you already use.

It's just email

No new app to learn, no login, no tab to live in. If you can forward an email, you can use Slung.

No implementation

Start in 60 seconds. No onboarding calls, no IT project, no weeks of setup before value.

No annual contract

Free to start, pay per seat when you're ready. No procurement, no lock-in — cancel anytime.

The Excel is yours

Everyone else guards their model. We hand over a fully editable Excel you can take anywhere.

Garden-style apartment community
High-rise apartment tower

It gets to know you

The more you use it, the more it’s your underwriting.

Slung learns how you underwrite — so the model comes back the way you’d have built it, and leaving means starting over.

Remembers your defaults

Your assumption defaults, expense reclassifications, and decision thresholds — applied automatically next time.

Learns from your edits

Every assumption you change in a model teaches Slung how you think — no forms to fill in.

Frees you to judge

Stop typing numbers. Spend your time on the call that matters — whether to pursue the deal.

Built by operators

Built by people who’ve underwritten the deals.

A real estate operator and an applied-AI scientist, building the underwriting layer for multifamily.

Lawson Wong

Lawson Wong

CEO

Real estate operator across acquisitions, asset management, and investor relations. Previously a Managing Director at Vibrant Cities, and other roles at Terreno Realty, PGIM Real Estate, and Morgan Stanley. BA in Economics at Harvard University.

Bill Shi

Bill Shi

CTO

PhD in Applied Math at The University of North Carolina at Chapel Hill. Former Amazon Applied Scientist, Machine Learning architect at TigerGraph, and CTO of an AI agent platform. Deep expertise in AI/LLMs and production ML systems.

What teams say

Multifamily teams move faster on Slung.

Slung cuts our underwriting from hours to minutes. The model is institutional-grade and easy to adjust.

Jordan Y.Acquisitions Associate

The Excel we get back is accurate enough to stress assumptions and run scenarios on the spot.

Eric B.Managing Partner

Instead of building models, I spend my time evaluating opportunities and making recommendations.

Elizabeth G.Underwriting Associate

Pricing

Start free. Scale by deal volume.

Analyze 8x the deals. The one you don't could leave millions on the table.

Free
Free
Up to 3 deals

Forward a deal and get back an institutional-grade underwriting model.

Start Free
Includes:
  • Up to 3 deals
  • Automated underwriting & returns by email
  • Dynamic Excel model attached
  • Property data & T-12 overview
Most popular
Starter
$99/mo
Billed monthly · per seat

For active investors and small teams underwriting a steady deal flow.

Get Starter
Everything in Free, plus:
  • 10 deals per month
  • Full market data, neighborhood insights & rent comps
  • Category-level market expense benchmarks
Pro
$299/mo
Billed monthly · per seat

For acquisitions teams running high deal volume across markets.

Get Pro
Everything in Starter, plus:
  • 80 deals per month
  • Priority processing
  • Team workspace & shared deals
Enterprise

Unlimited deals, SSO, custom integrations, and volume pricing for large teams.

Contact Us

Underwrite your next deal in minutes.

Forward a deal to sam@slung.ai and see the model come back.

Free to start · No credit card required · Get started in 60 seconds
SlungAI Logo

Subscribe

Subscribe to our newsletter for exclusive updates, insider tips, and offers delivered straight to your inbox.