Investor overview · Seed · Confidential · 2026
Enterprise-Grade AI
for the Real Estate
Profession.
LevelXero is an AI brokerage: the listing agent's full workflow, automated end to end, with a licensed broker accountable for every decision that binds. The transaction becomes structured data the moment it begins. The lender receives a MISMO 3.4 payload before the borrower's phone buzzes.
10 microservices · 1,817 tests
MISMO 3.4 · Outbox-delivered
San Antonio · Indianapolis · Charlotte
The number that matters
Commission is the cost of acquisition.
Adjacent services are the business.
Every residential transaction generates a predictable cluster of downstream services. Today, a brokerage captures the commission and sends the rest elsewhere. LevelXero captures both: the commission opens the relationship, and the structured transaction record makes every adjacent handoff instant and frictionless.
$3,800
average commission per transaction
(2.5-3% on $430K median sale)
Industry standard · Thin margin
$5,500
in adjacent services per transaction
(mortgage origination alone)
Currently going to third parties
$9,300
total revenue per transaction when adjacent services are captured: mortgage origination, title, escrow, insurance, home warranty
LevelXero's full unit · 2.4x commission alone
<$10
compute cost per transaction file vs. $150-300 in traditional agent overhead
Per-file economics at scale
What the platform does
Six jobs a listing agent does.
All of them.
The AI carries the labor. The professional holds the authority. A licensed broker reviews and remains accountable for every binding transition, while the machine runs the workflow end to end.
01
Lead captureQualifies inbound inquiries, books showings, structures the contact into the transaction arc.
02
Listing creationAddress and photos become a complete draft: copy, comps-based price, jurisdiction disclosures, MLS-ready fields.
03
Offer analysisEach offer scored on price, terms, contingencies, financing strength, and timing. The seller gets a ranked brief, not a PDF stack.
04
Counter draftingGiven seller priorities, the AI drafts the counter with price, terms, and rationale. Approved in a tap.
05
Deadline trackingInspection, financing, appraisal, title: every contingency clock tracked from execution. Nothing expires unnoticed.
06
MISMO handoffContract executes: a MISMO 3.4 payload fires to the lender's webhook. No PDF. No re-keying. Underwriting starts immediately.
Proof
Not a deck. A demo.
The full transaction arc runs end to end in a local dev environment: listing creation through MISMO handoff, ten microservices, real webhook delivery. The UI is in active build. The pipe is ahead of it.
30s
contract draft, start to finish
vs. hours of agent labor
0s
MISMO handoff lag at close
vs. 24-48 hrs of PDF email
1:500+
broker-to-transaction ratio
vs. 1:50 traditional
1.8k
tests passing, zero skips
Go × 7 services · Python × 3
Business model
Three revenue lines.
Each one re-rates the multiple.
LevelXero starts as a brokerage and becomes infrastructure. The commission funds operations in Year 1. Adjacent services are the margin center from Day 1. Platform licensing to other brokerages is the Series B story: the MISMO pipe as a subscription, not a service.
Line 1 · Year 1
Commission revenue
2.5-3% per transaction
The expected line. Funds operations. Earns the right to the adjacent services relationship.
Line 2 · Margin center
Adjacent services
+$5,500 per transaction
Mortgage origination, title, escrow, insurance, home warranty. Each plugs into the same structured handoff. Each nets 2-4x the commission margin.
Line 3 · Series B re-rate
Platform licensing
MISMO pipe as SaaS
Other brokerages subscribe to the structured handoff infrastructure. Converts the multiple from brokerage (1-2x revenue) to fintech (8-12x ARR).
Why this becomes infrastructure
MLS knows what sold.
LevelXero knows how.
For the first time, the full transaction record exists as structured data: not just the outcome, but the arc, the timing, the terms that moved, and the terms that held. A dataset no one else can build, because no one else owns the origination point.
-
1
Data flywheel
Every transaction trains the next one. Pricing accuracy, counter-strategy, contingency outcomes. The model improves with volume in a way GPT wrappers do not. The first 1,000 transactions are the asset.
-
2
Agent network effects
Buyers' agents who close with LevelXero get the fastest lender handoff in the market. Repeat buyers route through the platform. Each closed transaction deepens the relationship on both sides.
-
3
Adjacent services density
Once title, escrow, and origination plug into the same structured handoff, switching costs become real. The transaction record is not portable: it lives in the append-only ledger that only LevelXero owns.
Market
Three cities. One proof.
Then everywhere it looks like them.
The go-to-market strategy avoids coastal markets where eXp and Compass compete on brand and volume. The Tier 1 targets: San Antonio, Indianapolis, Charlotte: high transaction volume, low tech-brokerage penetration, significant first-time buyer population, and growing lender infrastructure. Adjacent services already exist in each market, ready to plug in at signed contract.
$100B
annual US residential commission pool
5M+ transactions per year
TAM · Commission alone
$170M
serviceable obtainable market at 6% share across three target cities including adjacent services revenue
SOM · Commission + adjacent
Competition
eXp and Compass are agent businesses.
eXp Realty is a distribution play: they give agents tools to close more deals. The agent is still the product. Compass gave agents software. The agent is still the product. Neither company has eliminated the labor of the listing agent's workflow; both have made it slightly more convenient.
LevelXero replaces the labor entirely. The licensed broker is not the bottleneck: the broker is the backstop. The AI is the operator. This is a different bet from "better tools for the agent" and it produces a different cost structure: <$10 per file vs. $8,000-15,000 in agent fees on the same transaction.
Team
The person building this has built it before.
Nicole Beaulieu
Founder · CEO · CTO
Six years at Figure Technologies, architecting the embedded lending platform behind 100+ private-label partnerships. The platform drives $1B+ in monthly loan volume. Joined as Principal Engineer, promoted through Director, VP Engineering, and CTO. The lender side of this transaction: already built, at scale, under production load.
Inventor on 25+ patents across lending, digital assets, and gaming. Principal inventor on a blockchain-based mortgage assignment registry. PhD, Computer Science (UNR, 2025); the dissertation formalized 30 years of building infrastructure that other companies' products run on top of.
The brokerage side is what is being built now. The technical architecture is not a new idea applied to real estate: it is a direct extension of the lending infrastructure already built for Figure's 100+ partners.
Top 50 Women in FinTech · 2024
PhD, CS · UNR 2025
MS, HCI · Iowa State 2018
25+ patents
Figure · 6 yrs · CTO 2024-25
Seed round · 2026
Raising Seed
Contact nicole@levelxero.co to receive the term sheet
Team
Hire the first two operators: a licensed broker of record and a founding market manager for launch city one.
Market launch
First 50 transactions in San Antonio. Adjacent services contracts signed. Data flywheel starts turning.
Infrastructure
Production hardening, compliance layer, licensing in two additional jurisdictions, lender partnership agreements.
Talk to the founder →