AdHome — Deep Dive Flows

Background checks & safety, go-to-market timeline, fee structure breakdown, platform evolution, vendor ecosystem, and AI learning loops.

Start/End
User Action
Decision
System
AI Agent
Outcome
Data
Legal/Compliance
Vendor
Money
Background Check & Safety
GTM Timeline
Fee Structure
Platform Evolution
Vendor Ecosystem
AI Learning Loops
Rent-to-Own Path

Background Check & Safety Flow

Tiered verification escalates with risk level. Browsing is open; in-person contact requires full verification. Both buyers and sellers are verified before any physical interaction.

Progressive Verification Tiers

User arrives at AdHome
Browse listings & search No checkZero friction entry -- anyone can view listings, photos, and neighborhood data
Save favorites / enable notifications Email onlyEmail verification required to create account
What type of showing?
Virtual Showing ID VerifiedPhoto ID already confirmed -- access to 3D model and virtual tour
Access grantedAI-guided virtual walkthrough; no physical risk
Access method?
AdHome ContractorLicensed showing agent present. Verifies photo ID match at door. GPS tracked.
Smart LockboxID scan at lockbox verifies identity. Entry logged and timestamped.
Third-Party VerificationNotary, UPS Store, or AdHome contractor verifies identity in person before access.
Make an offer Financial VerificationBank account verification + income verification + credit soft pull
Transaction proceeds with fully verified parties

Buyer vs. Seller Verification (Side by Side)

Buyer Verification

Buyer creates account
Email verificationCan browse, save, get notifications
Financial verificationBank, income, credit soft pull. Required to make offers.
Pre-qualificationAdHome internal assessment + lending marketplace pre-approval
Fully verified buyer

Seller Verification

Seller creates account
Email verificationCan begin property scan setup
Listing approvalProperty scan verified, disclosures reviewed, listing goes live
Fully verified seller

Safety Features During Showings

GPS Tracking

Opt-in GPS tracking during all in-person showings. Location shared with emergency contact and AdHome monitoring.

Check-In / Check-Out

Buyer and seller confirm arrival and departure. Missed check-out triggers automated wellness check within 15 minutes.

Emergency Protocol

In-app emergency button contacts 911 with location. Simultaneously notifies AdHome safety team and emergency contacts.

Real-Time Monitoring

When AdHome contractor is present: live status updates, showing duration tracking, post-showing safety confirmation.

Photo ID Match at Door

For contractor-assisted showings: agent verifies visitor's face matches uploaded ID before entry. No match = no access.

Showing History Audit

Complete log of every showing: who, when, duration, check-in/out times. Available to both parties and law enforcement if needed.

Recommended for in-person showings: Physical third-party verification (notary, UPS Store, or AdHome contractor) is strongly recommended before any in-person showing. This adds a layer of human identity confirmation beyond digital checks alone.

Go-to-Market Timeline

Month-by-month milestones from April 2026 through Year 2, with key decision gates, system launches, and funding milestones.

Year 1: Foundation to Bay Area Launch (April 2026 -- March 2027)

APR
2026
Incorporate (DE C-Corp) Broker license filed 3 provisional patents MVP architecture defined System 1 (Identity) started
MAY
2026
System 1 functional System 2 (AI Core) in dev ToS + Privacy Policy AI training data disclosure Users can create accounts and verify identity
JUN
2026
GATE: Broker license received System 2 (AI Core) functional System 8 (Negotiation) in dev Fair Housing bias audit Three AI agents can hold conversations; negotiations enabled
JUL
2026
Private beta (10-20 users) System 8 (Negotiation) live System 4 (Listing) live Agent recruitment begins First seller lists a property; AI negotiation in controlled testing
AUG
2026
Expanded beta (50-100 users) System 5 (Buyer Qual) live System 15 (Agent Marketplace) GATE: First transaction initiated
SEP
2026
GATE: First completed transaction 100+ registered users First closed deal through AdHome; transaction fee collected; agent feedback loop active
OCT
2026
Public launch (Bay Area) Marketing spend begins System 9 (Contract) live Seed fundraising initiated Platform open to all Bay Area users; pitch deck ready
NOV
2026
200+ users, 30+ listings System 6 (Search & Matching) UAD 3.6 compliance deadline Revenue run-rate: $5K-10K/month; lending partner talks advanced
DEC
2026
GATE: Seed round closed ($1.5-3M) 300+ users System 17 (Narrative) in dev Funding secured; 12+ months runway; holiday iteration sprint
JAN
2027
Spring season marketing push First hires (CS + Engineer) System 3 (Property Scan) started NMLS licensing complete Team grows to 5-6 people
FEB
2027
500+ users, 80+ listings System 7 (Showings) live System 12 (Lending) in dev Revenue run-rate: $20K-30K/month; 40+ agents on platform
MAR
2027
GATE: Year 1 targets 800+ users, 150+ listings LA expansion planning 40-50 total transactions; AI task completion 75%+; Year 1 revenue: $265K-459K

Year 2: California Scale (April 2027 -- March 2028)

Q1 Y2 (Apr-Jun 2027)

LA Metro Launch

  • Property Scan & Appraisal live (appraiser partnerships)
  • Digital twin / Home Ownership Lifecycle
  • 7-language multilingual support
  • 100+ cumulative transactions
  • Series A fundraising begins

Target: $50K+ MRR

Q2 Y2 (Jul-Sep 2027)

San Diego Launch

  • Lending marketplace live (RESPA-compliant)
  • Vendor network launched
  • Embedded insurance active
  • 250+ cumulative transactions
  • Engineering team: 8-10 people

Target: $100K+ MRR

Q3 Y2 (Oct-Dec 2027)

Sacramento Launch

  • Series A closed ($8-15M)
  • Investment property support
  • Advanced AI negotiation (learned strategies)
  • 500+ cumulative transactions
  • AI task completion: 85%+

Target: $150K+ MRR

Q4 Y2 (Jan-Mar 2028)

Orange County Launch

  • Data-as-a-Service product launched
  • 750+ cumulative transactions
  • First fully AI-managed transactions
  • Statewide coverage plan finalized
  • Out-of-state expansion evaluation

Target: $200K+ MRR (~$2.5M ARR)

Key Decision Gates

June 2026: Broker LicenseCannot launch without it. Contingency: education-only mode until received.
August 2026: First TransactionValidates that the platform can handle a real deal end-to-end.
December 2026: Seed FundingRequired for scaling. Without it: stay lean, grow organically.
March 2027: Year 1 Targets40-50 transactions, 75% AI task rate. If missed: reassess strategy.
Q3 2027: Series A$8-15M raise. Trigger: 150+ transactions, $500K+ ARR, proven unit economics.
Q4 2027: Full AI TransactionsFirst transactions completed entirely by AI, no human agent. Proves the thesis.

Funding Trajectory

Bootstrapped (Months 1-6)Team sweat equity + minimal comp. Target: 2-3 completed transactions as proof.
Seed Round: $1.5-3M (Oct-Dec 2026)Use: 2-3 engineers, marketing for spring 2027, licensing, 12-month runway
Series A: $8-15M (Q3-Q4 2027)Use: CA-wide expansion, engineering team of 8-12, lending marketplace, data infrastructure
Year 2 End: $2.5M+ ARR5 CA markets, 750+ cumulative transactions, clear path to profitability

Fee Structure Flow

How pricing works for sellers and buyers at every price point. Hybrid flat fee model with optional add-on services -- massive savings vs. traditional agents.

Transaction Tiers

Essentials

$2,995

flat fee per party

  • AI-guided listing + property scan
  • AI appraisal + virtual showing
  • Search & matching
  • AI negotiation (3-agent architecture)
  • Term sheet + purchase agreement
  • Document management
  • Multilingual support

Premium

$7,995

flat fee per party

  • Everything in Complete
  • Dedicated human transaction coordinator
  • Priority vendor scheduling
  • Monte Carlo negotiation simulations
  • First year HomeBase subscription included
Dual-platform discount: When both buyer and seller use AdHome, each receives a $500 discount -- incentivizing platform adoption on both sides.

Seller Fee Schedule by Price Bracket

Seller decides to list
Choose service tierEssentials | Complete | Premium
Property scan + listAI valuation, photos, virtual tour, disclosures auto-generated
Negotiate + accept offerAI handles negotiations 24/7 within seller's parameters
Pay at closing50% at purchase agreement signing, 50% at close. Deducted from proceeds.
Transaction complete
Price BracketAdHome FeeTraditional (2.5%)Dollar Savings% Savings
Under $500K$995$12,500$10,00580%
$500K - $750K$995$15,625$12,13078%
$750K - $1M$995$21,875$17,38079%
$1M - $1.5M$995$31,250$25,25581%
$1.5M - $2M$1,995$43,750$36,25583%
$2M - $3M$1,995$62,500$52,50584%
$3M+$1,995$75,000+$62,005+83%+

Buyer Fee Schedule by Price Bracket

Buyer begins search
Browse free, no commitmentAI learns preferences -- zero cost to explore
Get pre-qualifiedFinancial verification enables making offers
Choose tier + make offerEssentials | Complete | Premium
Pay at closingIf seller offers buyer agent commission: AdHome fee deducted, remainder rebated to buyer
Keys in hand
Price BracketAdHome FeeTraditional (2.5%)Dollar Savings% Savings
Under $500KFREE$12,500$12,50084%
$500K - $750KFREE$15,625$15,62581%
$750K - $1M$3,995$21,875$17,88082%
$1M - $1.5MFREE$31,250$31,25084%
$1.5M - $2M$995$43,750$37,75586%
$2M - $3MFREE$62,500$62,50087%
$3M+$1,995$75,000+$65,005+87%+

Savings at Key Bay Area Price Points

$500K Home
$25,000 traditional (both sides)
$4,490
AdHome (both sides)
Save $20,510 (82%)
$1M Home
$50,000 traditional (both sides)
$8,490
AdHome (both sides)
Save $41,510 (83%)
$1.5M Home
$75,000 traditional (both sides)
$13,490
AdHome (both sides)
Save $61,510 (82%)
$2M Home
$100,000 traditional (both sides)
$13,490
AdHome (both sides)
Save $86,510 (87%)
Post-NAR settlement buyer rebate: If a seller offers 2.5% buyer agent commission on a $1.275M home ($31,875), AdHome collects NO buyer fee. If the seller offers buyer agent commission, the FULL amount is rebated to the buyer as a closing cost credit. Net buyer cost: $0 out of pocket + $26,880 credit.

Add-On Services

Pro Photography$395 (25-40 HDR photos)
Photography + Drone$595 (photos + 5-8 aerials)
Matterport 3D Tour$495-$695 (by sq ft)
Virtual Staging$75/room (AI-generated)
Video Walkthrough$695 (cinematic 2-3 min)
Showing Contractor$150/showing or $595/5-pack
Expedited Processing$995 (priority + dedicated support)
Open House Hosting$350/event (licensed agent)
Neighborhood Report$49 (AI-generated deep analysis)
Premium Marketing$1,495 (photo + drone + video + staging + ads)

Platform Evolution

How AdHome capability grows from MVP through full autonomy -- what humans handle in each phase versus what AI handles, and the learning progression that drives the transition.

Three-Phase Capability Growth

Phase 1: MVP + Agent Assist

Months 1-6 (Apr-Sep 2026)

  • Identity & onboarding
  • AI agent core (3-agent architecture)
  • Basic listing creation
  • Buyer pre-qualification
  • AI-assisted negotiation
  • Agent marketplace (trojan horse)
  • Materials term sheet generation

AI task completion: 40-50%

Phase 2: Full Transaction

Months 7-12 (Oct 2026-Mar 2027)

  • Search & matching engine
  • Contract auto-generation
  • Trust & security (wire fraud)
  • Transaction narrative layer
  • Showing coordination
  • Escrow & inspection management
  • Lending marketplace

AI task completion: 65-75%

Phase 3: Full Autonomy

Year 2+ (Apr 2027+)

  • Property scan & AI appraisal
  • Digital twin lifecycle
  • Vendor network marketplace
  • Insurance integration
  • Investment property support
  • Data-as-a-Service
  • Agent-free transactions

AI task completion: 85%+

Human vs. AI: Task Transition by Phase

Task
Phase 1
Phase 2
Phase 3
Listing Creation
Human enters data, AI assists with descriptions
AI generates from scan data, human reviews
Fully AI-generated from property scan
Pricing / Valuation
Manual CMA data, agent guidance
AI valuation from scan + comps, appraiser review
AI-primary valuation, human review for edge cases
Negotiation
AI leads with agent monitoring. Human escalation for complex issues.
AI handles 80%+ of negotiations autonomously
Fully autonomous with learned strategies from transaction data
Showings
Agent-facilitated or self-guided
Virtual (AI) + contractor in-person + lockbox
Virtual AI tours dominant; minimal in-person needed
Legal Documents
Attorney drafts and reviews everything
AI generates, attorney reviews and signs
AI generates with attorney spot-check for complex cases
Escrow / Closing
External partner manages entirely
AI coordinates, partner executes
AI manages end-to-end with integrated partner
Lending
External referrals only
Embedded marketplace with AI comparison
AI auto-matches buyers to optimal lenders; manages conditions
Post-Close
Not available
Basic digital twin, manual updates
Full lifecycle: maintenance, insurance, value tracking, vendor management
Human-primary
Hybrid (AI + Human)
AI-primary

The Learning Progression

Agents onboarded (Trojan Horse)Agents bring transactions and teach the system through every override
Every agent action is loggedWhat they do manually, where AI fails, what decisions they make
AI learns from agent behaviorEscalation patterns, negotiation tactics, process judgment calls
AI task completion climbs40% -> 65% -> 75% -> 85% -> 95%+ over 2-3 years
Agent role shiftsFrom "doing the work" to "reviewing AI work" to "handling exceptions only"
Agent SaaS revenue peaks then declinesPeak Year 2, decline Year 3+ as AI replaces agent tasks
Full AI transactionsSome transaction types fully AI-managed by end of Year 2

Vendor Ecosystem

How vendors interact with the platform -- from onboarding and vetting through assignment, service delivery, rating, and payment. Each touchpoint generates revenue and data.

Vendor Lifecycle Pipeline

Onboarding

Application, license verification, insurance check, background check

Vetting

Credential review, reference checks, sample work evaluation, pricing verification

Assignment

AI matches vendor to job by location, specialty, availability, rating, and price

Service

Vendor performs work. Status updates tracked in real time. Quality monitored.

Rating

Both parties rate. AI analyzes outcome quality. Performance score updated.

Payment

Platform processes payment. 10-15% take rate retained. Vendor paid within 3 days.

Vendor Types & Transaction Touchpoints

Pre-Listing

Photographer
3D Scanner
Stager
Drone Operator
Videographer

Showings

Showing Agent
Open House Host
Lockbox Provider

Due Diligence

General Inspector
Pest Inspector
Roof Inspector
Sewer Scope
Foundation
Appraiser

Closing

Title Company
Escrow Officer
Notary
Attorney

Repairs & Improvements

General Contractor
Plumber
Electrician
HVAC
Roofer
Painter

Post-Close

Movers
Cleaners
Insurance
Utility Setup
Landscaper
Home Warranty

Revenue Capture at Each Interaction

Vendor InteractionTypical CostAdHome Take RateRevenue per Event
Professional photography$250-$65020-55%$50-$300 markup
3D / Matterport scan$400-$1,00010-20%$40-$200 markup
In-person showing$100-$15015-25%$15-$40
Home inspection$400-$70010-15%$40-$105
Repair services$1,000-$10,00010%$100-$1,000
Title & escrow$2,000-$4,000Partnership referral$500-$1,000
Moving services$2,000-$8,00010-15%$200-$1,200
Insurance placement$2,000-$4,000/yr premium10-15% commission$200-$600/yr recurring
Ongoing home services$3,000-$5,000/yr10%$300-$500/yr recurring

Vendor Quality Flywheel

Vendor completes service
Structured feedback collectedUser rating + AI outcome analysis (on-time, on-budget, quality score)
Performance score updatedWeighted average across all jobs. Recency-biased.
Score affects future assignmentsHigher scores = more assignments = more revenue for vendor
Score below threshold?Vendors below 3.5/5 after 10+ jobs enter probation; below 3.0 removed
Quality improves over timeNatural selection: best vendors get more work, worst are removed
Better vendor recommendationsUsers trust the platform; vendors compete on quality, not price alone
Market benchmarks for take rate: Angi (15-20%), Thumbtack (10-15%), Amazon Home Services (15-20%), TaskRabbit (15%). AdHome targets 10-15% -- competitive enough to attract quality vendors while capturing meaningful revenue.

AI Learning Loops

Detailed view of how each AI system improves through transaction data, agent behavior capture, and continuous feedback loops. Every interaction makes the platform smarter.

1. Valuation Model Training Loop

Property Valuation Accuracy Flywheel

Seller scans property
-->
AI generates valuation
-->
Property sells at X price
-->
Delta recorded
-->
Model recalibrated
-->
Next valuation is more accurate
Interior condition data: the killer advantageRoom-by-room condition scoring, fixture/appliance ID, surface material ID, system age, renovation history, LiDAR measurements, known defects
What no other AVM hasA 2,000 sq ft home with a renovated kitchen is worth more than an identical home with 1970s fixtures. Zillow/CoreLogic cannot tell the difference. AdHome can.
Scan TierExpected Median Error80% WithinZillow Comparison
Basic (20-40 min)8-12%+/- 15%Zillow Zestimate: ~6.9% median error (off-market, no interior data)
Standard (60-90 min)5-8%+/- 12%
Comprehensive (2-4 hr)3-6%+/- 8%
Comprehensive + Pro2-5%+/- 6%

2. Negotiation Pattern Learning

Negotiation Intelligence Engine

AI negotiates deal
-->
Strategies logged
-->
Outcome recorded
-->
Pattern analysis
-->
Strategy refined
What the AI Learns
  • Which opening strategies work at which price points
  • Optimal counter-offer timing (fast vs. deliberate)
  • When contingency flexibility matters most
  • Market condition impact on negotiation leverage
  • Multi-offer scenario optimal response patterns
  • Escalation clause vs. best-and-final effectiveness
Data Sources
  • Every offer, counter-offer, and response
  • Time between moves and final outcomes
  • Terms that close deals vs. terms that kill them
  • Agent overrides (what did the human do differently?)
  • Market velocity at time of negotiation
  • Property-specific factors (days on market, condition)

3. Matching Algorithm Refinement

Buyer-Property Matching Intelligence

Buyer sets criteria
-->
AI recommends matches
-->
Buyer interacts
-->
Implicit signals captured
-->
Buyer purchases home
-->
Model learns gap
The key insight: What buyers actually buy often differs from what they say they want. A buyer who says "3+ bedrooms, under $1M" might consistently spend time looking at 2-bedroom homes in a specific neighborhood at $1.1M. Implicit behavioral signals outperform explicit criteria for matching quality.
Time spent on listings
Photos viewed & re-viewed
Virtual tour behavior
Showing requests vs. passes
Post-showing feedback
Offer vs. no-offer after showing

4. Process Optimization from Transaction Data

Transaction Efficiency Engine

Transaction progresses
-->
Bottlenecks detected
-->
AI identifies patterns
-->
Proactive prevention
Problems Detected
  • Where do deals get stuck?
  • Which document requests cause delays?
  • What inspection findings kill deals?
  • Which lender conditions take longest?
  • When do contingency deadlines get missed?
Prevention Actions
  • Pre-collect documents AI knows will be needed
  • Warn about likely inspection issues from scan data
  • Route to faster lenders for time-sensitive deals
  • Escalate before deadlines, not after
  • Recommend contingency timelines based on actual data

5. Agent Behavior Capture (Trojan Horse Learning)

The Trojan Horse Intelligence Pipeline

Agents onboard onto the platform for its tools. Every action they take teaches the AI what it needs to learn to eventually replace them.

Agent uses AdHome tools for their transactionTransaction management, document generation, client communication
Every action is loggedManual overrides, AI suggestion acceptance/rejection, time allocation, decision patterns
AI categorizes agent actionsWhich are routine (automatable)? Which require judgment? Which are relationship-driven?
Routine Tasks

AI automates first. Scheduling, document prep, status updates, data entry.

~50% of agent work

Judgment Calls

AI learns next. Pricing advice, negotiation tactics, disclosure interpretation.

~35% of agent work

Relationship / Emotional

Hardest to replace. Hand-holding, crisis management, trust building.

~15% of agent work

AI task completion rate climbs as each category is conquered
Measure: AI-vs-Agent task completion ratesTrack monthly. When AI matches agent quality on a task category, remove agent requirement.
Agent role evolves: doer -> reviewer -> exception handler -> unnecessary

6. Appraisal Learning Loop (Phase 2+)

AI-to-Appraiser Convergence

AI drafts appraisal
-->
Appraiser reviews
-->
Adjustments logged
-->
AI learns from corrections
-->
Fewer adjustments over time

Every appraiser adjustment is a training signal. If the appraiser consistently adjusts condition scores upward for a certain renovation type, the model learns it was undervaluing that renovation. If the appraiser adds or removes comps, the model learns which comp selection criteria matter. Over thousands of appraisals, the AI converges toward appraiser-quality judgment while retaining its advantages in data richness and consistency.

The Compound Data Moat

Every transaction adds data
Scan data + negotiation data + pricing outcomes + vendor performance + agent behavior
All six learning loops improve simultaneouslyValuation, negotiation, matching, process, agent capture, appraisal
Better outcomes attract more users
More users = more data = better outcomes
Compounding moat: competitors cannot replicate without processing the same volumeFirst 1,000 scans/market = largest accuracy gains. 50,000+ scans statewide = industry-leading.

Zillow

Has photos but no structured condition data, no system-level detail, no defect documentation

Matterport

Has 3D geometry but no condition scoring, no valuation integration, no outcome tracking

CoreLogic

Has public records and MLS data but zero interior condition data

Automax

Captures interior data for appraisals but has no listing platform, no transaction data, no digital twin

AdHome is the only platform positioned to combine interior condition capture, transaction outcome tracking, digital twin persistence across ownership changes, and valuation model training in a single loop. This is the moat.

Rent-to-Own: The Secret Weapon

Alternative paths to homeownership for people who can afford a home but can't qualify traditionally. No competitor addresses this.

Regulatory Tailwind: As of January 2, 2026, FHFA mandates alternative data (rent, utilities) in government-backed mortgage underwriting. VantageScore 4.0 can score 33 million previously "credit-invisible" consumers. This changes everything.

The Problem

$3,055
SF Average Monthly Rent
$2,200
Equivalent Mortgage Payment
23%
CA Households That Qualify

Millions of renters pay more than a mortgage would cost — but can't qualify. AdHome bridges this gap.

The AdHome Graduated Pathway

Renter can't qualify traditionallyGood payment history, insufficient credit score or down payment
AI assesses alternative dataRent history, utility payments, bank account patterns, employment stability
Which pathway fits best?

Path A

Lease-to-Own

Rent with a portion going toward purchase price. Option to buy at locked-in price.

  • 1-5% option fee (applied to purchase)
  • 10-25% of rent credited toward price
  • 1-3 year option period
  • Price locked at signing
  • AI manages the entire lease-option contract

Path B

Seller Financing

Seller acts as the bank. Buyer pays seller directly with negotiated terms.

  • Dodd-Frank: 1 property/year safe harbor
  • No ability-to-repay requirement
  • AdHome structures the deal
  • AI manages payments and compliance
  • Deed of trust protects seller

Path C

Graduated Qualification

AI coaches the renter toward mortgage qualification while they rent.

  • AI tracks payment history as evidence
  • Credit improvement coaching
  • Down payment savings plan
  • Auto-connects to lending marketplace when ready
  • Seamless transition from renter to buyer

The Graduated Qualification Flow

Renter enters AdHome pathway
Phase 1: Assessment
AI analyzes financial situationIncome, rent history, debts, credit gaps, savings rate
Personalized roadmap generated"You're 14 months from qualifying. Here's the plan."
Phase 2: Active Coaching
Monthly AI check-insCredit score tracking, savings progress, debt paydown coaching
Payment history documentedEvery on-time rent payment builds the case for qualification
Progress dashboardVisual tracker: "78% of the way to qualification"
Phase 3: Pre-Qualification
Qualification thresholds met?
Auto-connect to lending marketplaceRent history + alternative data submitted to lenders
Phase 4: Transition
AI matches properties within budgetAlready knows preferences from browsing during rental phase
Standard buyer flow beginsFull AdHome transaction experience
Homeowner.From renter to owner — guided every step by AI.

Why This Is the Secret Weapon

No Competitor Does This

Homa, Redfin, Opendoor, Zillow — none address the qualification gap. AdHome creates buyers that don't exist yet for other platforms.

Creates a Buyer Pipeline

Every renter in the pathway is a future qualified buyer. Predictable pipeline of transactions 12-36 months out.

Longer Relationships = More Data

1-3 year coaching relationships build deep user data, trust, and loyalty. Higher LTV than one-time transactions.

Social Impact Story

Making homeownership accessible to underserved communities. Powerful for branding, investor appeal, and press.

Seller Benefits

Above-market rent during lease period + guaranteed buyer at the end. Sellers get income now and a sale later.

5 Million Americans

Estimated number who would benefit from alternative credit scoring for mortgage qualification. Massive addressable market.

Market timing: FHFA's January 2026 mandate for alternative data in underwriting is the biggest regulatory tailwind for this feature. VantageScore 4.0 acceptance by Fannie/Freddie means rent history can now actually count toward mortgage qualification. This was impossible two years ago.