AI consulting · Real estate
AI consulting for CRE lenders, brokers and investors
Native helps commercial real estate lenders, brokers and investors put AI agents into origination and deal flow: finding qualified owners, taking in deals, collecting documents and preparing files for underwriting. For Hybrid, a commercial real estate lending platform, Native built a lead engine that finds scored owner-occupied leads for $0.12 to $0.24 each and a deal handoff that carried a $5.33M deal into the loan system automatically.
Featuring insights fromShaun Devan · Founder & CEOUpdated · 3 min read
Where AI has an impact in real estate
Owner-occupied lead generation
Businesses that own their buildings found by industry or territory, scored and graded for your programs.
Program matching
Each deal matched to the loan programs and capital sources whose size and leverage limits fit it.
Deal intake
Submissions classified against your credit manual on arrival, with program fit checked first.
Document collection
Stage-specific needs lists sent, chased and checked until the package is complete.
Rent roll and OM reading
Rent rolls, operating statements and offering memoranda read and summarised in your format.
Underwriting prep
Financials spread and a first-draft memo written for the underwriter to edit.
Broker and partner portals
White-label platforms where partner brokerages submit deals and track commissions.
Support and status
Partner and borrower questions answered from help content, with no access to other parties' deals.
Where AI has an impact in commercial real estate
CRE runs on relationships and on data that is scattered, expensive and often wrong. Brokers spend hours finding owners worth calling, lenders wait weeks for a complete package, and investors read rent rolls and offering memoranda one at a time.
Agents change the cost of each of those steps. They search and score property and business records, read the package as it arrives, check it against your programs and keep every party current, so your team spends its time on deals that can close.
Lead engines that respect data costs
Property and contact data is the largest running cost of any origination engine, so the design starts there. Agents filter out ineligible properties before any paid lookup, cache every result with its own freshness window, and resume an interrupted job without paying twice.
Each lead is scored on property fit, value against your loan programs and how reachable the owner is. Owner-occupancy is checked against several signals rather than one, because the property record's own flag is often wrong. For an SBA lender, the loan-program fit bands are part of the scoring, so a $3M owner-occupied building is matched to the programs that can actually fund it.
From deal submission to the loan system
A broker or borrower submits a deal in about a minute. Agents classify it against your credit manual, build the needs list for its stage, program and asset class, chase the documents and validate each one on arrival, then hand the complete package to your loan operating system and alert the processor.
The first message to any new party waits for a person's approval, and follow-ups in that thread run on their own. Agents never quote, negotiate or change terms.
What agents prepare, and what stays with your team
| Work | Agent | Your team |
|---|---|---|
| Lead sourcing and scoring | Searches, filters, scores and grades each owner | Chooses who to call |
| Deal intake | Classifies the deal and checks program fit | Accepts or declines |
| Document collection | Builds the needs list, requests and checks each document | Approves the first contact |
| Underwriting prep | Spreads financials and rent rolls, drafts the memo | Underwrites and prices |
| Terms and negotiation | Never involved | Decides |
What an AI engagement in real estate looks like
We start with your credit manuals, program guides and how deals reach you today, and turn them into structured rules agents can follow and your team can edit. The first agent, a lead engine or the document chase, is live within weeks. Underwriting prep, investor matching and pipeline reporting follow. The same approach serves commercial lenders outside real estate.
Case study · Hybrid
Hybrid found scored CRE leads for cents each and handed deals to its loan system automatically.
Native helped Hybrid, a commercial real estate lending platform, build an owner-occupied lead engine and a white-label platform for partner brokerages. Leads cost $0.12 to $0.24 each, deals are submitted in about a minute, and the first automated handoff carried a $5.33M deal into the loan system.
The challenge
Hybrid needed a steady flow of owner-occupied commercial property leads that fit its loan programs, and a way for partner brokerages to submit deals without re-keying them. Property data was the largest cost, and the property records often mislabelled owner-occupancy.What we built
- A lead engine with industry and territory modes that filters ineligible properties before any paid lookup, verifies owner-occupancy from three signals and grades each lead High, Medium or Low.
- A multi-tenant white-label platform for partner brokerages, with branded domains, role-based access and commission tracking.
- A deal submission flow that invites the borrower to a view-only portal and hands accepted deals to the loan operating system with an alert to the processor.
The result
Platform users grew from 15 to 25 in the three weeks after the first partner brokerage joined, and the first deal through the automated handoff was $5.33M.Frequently asked questions
How is AI used in commercial real estate?
In origination and deal flow: finding and scoring owners, taking in deals, collecting documents, reading rent rolls and preparing files for underwriting. Pricing and negotiation stay with people.
Can AI generate commercial real estate leads?
Yes. For Hybrid, Native built a lead engine that finds and scores owner-occupied leads for $0.12 to $0.24 each in data cost, filtering out ineligible properties before paying for any lookup.
What does an AI consultant do for a CRE lender?
An AI consultant turns your credit manuals and program guides into rules agents can follow, then builds agents for intake, document collection and underwriting prep inside your systems. Native's forward-deployed engineers build and run them until your team takes over.
Can AI underwrite a commercial real estate loan?
AI can spread the financials, read the rent roll and draft the memo. The underwriting decision, pricing and terms stay with your team.
How quickly can a CRE firm see results from AI?
A lead engine or document chase is usually in production within weeks. A full deal pipeline, from intake to the loan system, follows within months.