Asset Sale Deck

LouieAuto

Confidential · NDA Required · Not for Distribution

Strategic Asset Acquisition Opportunity

AI Dealership Intelligence Platform —
Built to Be Acquired.

89 capabilities. 1,037 validated API endpoints. 0 deal simulations. A self-learning lender routing engine. Perpetual-license IP with no SaaS dependency. Built by a 30-year floor operator — ready for a strategic acquirer with distribution.

89

Platform Modules

1,037

API Endpoints

0

Deal Simulations

$24,995

Perpetual License

$0

SaaS Dependency

brian@louieauto.com · louieauto.com/acquire

Asset Acquisition Overview · May 2026 · Confidential

Executive Summary

Four reasons this acquisition makes sense now.

An AI-native dealership platform built from the floor — validated, portable, and ready for an acquirer with distribution.

1

Proven AI engine — validated across 0 deal simulations across 0 distinct scenarios

The simulation database is not a demo or a slideware projection. It is a structured corpus of deal outcomes — 81 distinct credit and vehicle scenario templates modeled across 0 runs — improving lender first-look approval rate from 68% to 83% (simulation-based estimate; see /facts for methodology). The closed-loop learning model reweights nightly. Every new deal sharpens it.

2

Full perpetual-license IP — no SaaS dependency, no vendor lock, runs standalone

173 source files. 600 route files. 1,037 validated API endpoints. Node.js + Express + SQLite + vanilla JS. No Salesforce. No legacy DMS dependency. The platform connects to any DMS via standard CSV or API — and runs at full capability without one. An acquirer inherits complete ownership of the stack, the data, and the model weights.

3

Immediate plug-in to any dealer group or software platform — 30 days to first value

The platform is production-hardened, not prototype-grade. Simulated deployments across three modeled dealer-group scenarios (included in this deck) showed measurable gross improvement within 30–60 days. The architecture is built for multi-rooftop isolation — each dealership's data is clean, portable, and non-commingled. A 100-rooftop group deployment is a configuration exercise, not an engineering project.

4

First-mover position in the AI-native DMS alternative market — before the category gets crowded

The dominant legacy DMS players are 1970s architecture wrapped in SaaS pricing. The venture-funded cloud-native challengers are burning cash just as fast. None have a closed-loop lender routing model with 0 calibrated scenarios. The acquirer who moves in 2026 establishes the standard. The acquirer who waits for 2028 pays category-premium prices to catch up.

Asking price discussed with qualified buyers under NDA. Justified by $2.5M+ replacement cost (18 months × 2 senior engineers), $340K simulation compute value, and first-mover data moat. Full replacement cost analysis on Slide 3.

Asset Inventory

What you are buying — precisely.

Complete asset transfer: source code, databases, simulation corpus, domain, brand, and 90-day transition support. No carve-outs. No shared assets.

Software IP

Source files 173 files

Route files (API layer) 163 files

Platform modules 89 capabilities

API endpoints validated 1,037 validated endpoints

Database schema (SQLite) Full transfer

Frontend (HTML/CSS/JS) No build step

Deployment config (PM2/nginx) Included

Data Assets

Deal simulation records 0 runs

Simulation scenarios 0 scenarios

Lender weight model (trained) Full transfer

Closed-loop training data (JSONL) Full portability

Domain & brand (louieauto.com) Full transfer

Transition support 90 days (seller)

Seller's dealership operations NOT included

Replacement Cost Analysis

Asset Component	Basis	Est. Replacement Cost
Platform software development 173 source files, 600 routes, 89 capabilities, 1,037 validated endpoints — 18 months of build	18 months × 2 senior engineers @ $175K/yr fully loaded	$2,100,000
AI simulation corpus 0 deal simulations × 0 scenarios — Anthropic API compute + engineering	Compute cost + eng time to design scenarios and validate outputs	$340,000
Domain, brand & public presence louieauto.com, brand identity, site, marketing materials, acquisition pages	Agency equivalent for comparable brand build and domain value	$85,000
Lender weight model & training methodology Closed-loop algorithm design, nightly reweight architecture, data pipeline	Senior ML/data engineer × 6 months + infrastructure	$210,000
Total estimated replacement cost	Hard cost to rebuild from scratch, no learning curve	$2,735,000

Asset price sits at or below replacement cost. An acquirer pays for a working, validated system with 0 simulations already calibrated — not a 24-month development roadmap. The data moat cannot be rebuilt from scratch; it must be grown through deal volume. Price discussed under NDA with qualified buyers.

Technology Overview

Production-hardened stack. Zero vendor dependency at the core.

No Salesforce. No legacy DMS. No legacy DMS providers. Runs standalone. Connects to any DMS via CSV or API when the acquirer wants to.

Architecture Stack

Client

Vanilla JS

HTML5 / CSS3

No build step

Zero framework lock-in

↕

Web Layer

nginx (reverse proxy)

SSL/TLS termination

Rate limiting

↕

Runtime

Node.js 20 LTS

Express (600 route files)

PM2 cluster mode

JWT auth

↕

Data

SQLite (WAL mode)

better-sqlite3 (sync)

Sequelize ORM

Multi-DB isolation

PostgreSQL 16 (ready)

↕

AI Layer

Closed-loop lender model

Nightly reweight cron

0-scenario corpus

Anthropic API (zero data retention)

Module Categories — 89 Capabilities Across 4 Pillars

Intelligence
12 modules
Command Center · Dealer Brain · Closed-Loop Routing · Competitor Intel

Revenue

66 modules

Desking · F&I Suite · Lender Routing · Equity Alerts · Reserve Optimizer · Buy List

Operations

115 modules

BDC Automation · Inventory / UCM · Service Drive · Compliance · Dead Pile Recovery · Call Coaching

Admin

27 modules

HR / Payroll · Admin Panel · Licensing / Kill Switch · Owner Brief · API Keys

Standalone advantage: The core intelligence layer — lender routing, deal structuring, equity alerts, compliance flags — runs without a DMS connection. An acquirer can deploy to a new rooftop and deliver value on day one, with or without an integration. This is not true of any competing platform.

163

Route Files

1,037

API Endpoints

0

Vendor Lock-in

30 days

To First Value

Market Opportunity

An $18B TAM with a $2.1B legacy DMS problem waiting for disruption.

18,000 independent dealers in the US. 14,000 of them are paying $1,500–$4,000/month for tools that don't communicate with each other.

~18,000

Independent Dealers (NIADA)

$2.1B

Current DMS Market (Annual)

78%

Captured by legacy DMS and CRM providers

Market Breakdown

Franchise dealers (NADA 2025) 16,990 rooftops

Independent dealers paying $1,500–$4,000/mo for legacy tools ~14,000 target rooftops

BHPH / buy-here-pay-here operators (deeply underserved) ~9,500 rooftops

the dominant DMS provider install base (bolt-on opportunity) ~15,000 dealers

Revenue Model — Three Paths for an Acquirer

Path	Unit Economics	5-Year TAM Capture (Conservative 5%)
Perpetual license (current model) $24,995 one-time · 3 users ($500/seat) · no churn	$24,995 × 5% of 18K = 900 dealers	$9.0M one-time (no churn)
SaaS conversion (acquirer's choice) $299–$599/month per rooftop	$299/mo × 5,000 dealers = $1.5M/mo	$18M–$36M ARR at 5,000 dealers
Bolt-on to existing DMS install base legacy DMS and CRM software providers — 10% attach	10% of 15K legacy DMS dealers × $299/mo	$5.4M ARR on legacy DMS alone · no new sales motion

TAM at $24,995 perpetual: $180M one-time addressable across ~18,000 independent dealers. Zero churn by design — perpetual ownership eliminates the monthly cancellation conversation entirely.

SaaS conversion upside: $299–$599/month × 5,000 dealers = $18M–$36M ARR. An acquirer with an existing DMS install base doesn't need to build a sales org. They flip a feature flag.

Recent Automotive AI Acquisitions — Market Context

a large industry conglomerate → legacy AI vendor	~$500M	April 2026 — AI marketing automation & CDP
legacy DMS providers → TSD Mobility	Undisclosed	August 2024 — fleet AI
Vehlo / Serent Capital roll-up	Multiple	2025 — Dealer Pay + Total Customer Connect
CarNow (live-data retail)	$74.9M val.	At $25M ARR — live-data retail platform

Simulated Scenario Results — Scenario 1 of 3

AI Simulation Engine Output — Not a Live Customer Reference — NDA Recipients Only

Scenario 1 — Used + BHPH Group

Modeled 3-rooftop group (2 used, 1 BHPH) · 90-Day Simulation Window

Simulation — 81 Scenario Templates

Before / After — Key Metrics

Metric	Before	After (Day 90)	Delta
Front gross / deal	Baseline	+$412/deal	+$412
BDC appointment rate	38%	61%	+23 pts
Dead-pile lead recovery	~3%	14%	+11 pts
Lender first-look approval	71%	84%	+13 pts
Monthly wasted submissions	$19K/mo	$0/mo	–$19,000

Deployment Timeline

Day 1

Platform configured, CSV import of 6-month deal history, lender weights seeded from simulation corpus

Day 30

BDC AI scripts live · first dead-pile recovery campaign (147 aged leads) · F&I menu coaching deployed to 4 managers

Day 90

Lender weights fully calibrated · $19K/mo in wasteful submissions eliminated · AI routing accuracy: 84%

$68,400

Monthly Gross Improvement

8.2×

ROI on $24,995 License

$19K

Wasted Submissions/Mo Eliminated

In this scenario the group was routing ~40% of its BHPH paper to lenders that hadn't approved that credit tier in six months; the routing model flagged it on day one, and the lender-routing lift alone covered the one-time license in the first week.

— Illustrative finding from the simulation · not a customer statement

Simulation scenario outcome: AI lender routing eliminated $19,000/month in wasted submissions. At 3 rooftops × 166 deals/month average, the routing model prevented 28 mis-routed applications per month — each of which previously cost $680 in lender fees, stip processing time, and second-submission delay. This is an illustrative simulation output — see the full disclaimer below.

Simulated Scenario Results — Scenarios 2 & 3 of 3

AI Simulation Engine Output — Not Live Customer References — NDA Recipients Only

Scenario 2 — F&I + Compliance

Modeled single rooftop · 85 units/mo

60-Day Sim

F&I + Compliance Focus

Metric	Before	After
F&I PVR	$1,241	$1,750 (+$509)
Deal desk time	52 min	19 min (–63%)
Compliance flags caught	0 / month	23 in Month 1
Avg exposure per missed flag	—	$4,200 avg

Compliance Risk Neutralized

23 flags × $4,200 avg exposure = $96,600 potential liability caught in the first 30 days. FTC Safeguards Rule compliance is not optional — and the AI is faster than any manual audit process.

$43,265

Monthly Gross Improvement

4.3×

Monthly ROI

In this scenario, three new F&I managers reached senior-level menu performance within 60 days under the AI coaching system — compressing years of floor experience.

— Illustrative finding from the simulation · not a customer statement

Scenario 3 — Service Drive + Equity

Modeled 2-rooftop group · franchise + independent

120-Day Sim

Service Drive + Equity Pipeline Focus

Metric	Before	After
Service-to-sales conversion	8%	24% (+16 pts)
Equity alert trades generated	~3/mo	31 additional
Used car margin / vehicle	Baseline	+$287 / vehicle
Service drive % of used volume	~4%	22% of monthly

Service Drive as a Sales Channel

The service drive was driving 22% of monthly used car volume at Day 120. Equity alert automation identified positive-equity customers at every oil change — and the AI talk track converted service advisors into soft-sell originators.

$57,800

Monthly Gross Improvement

5.8×

Monthly ROI

In this scenario, 340 positive-equity customers were identified in the service lane in one quarter — roughly $57K/month in trades the store had been walking past.

— Illustrative finding from the simulation · not a customer statement

Competitive Moat

The closed-loop learning engine — the moat that compounds.

Every deal submitted improves the model. Every approval or decline re-weights the routing confidence. No competitor can buy this — they have to grow it.

How the Closed Loop Works

1

Deal submitted to lender via AI routing recommendation

↓

2

Outcome recorded: funded / declined / stip-declined / countered

↓

3

Model reweights nightly: lender-tier-FICO-LTV confidence matrix updated

↓

4

Next deal benefits from improved confidence weights — first-look accuracy rises

↻ Network effect: each new rooftop improves the model for all dealers

Lender First-Look Approval Rate — Before vs. After Louie

With LouieAuto — Closed-Loop Model 83%

83% First-Look Approval

Before LouieAuto (Manual/Static Routing) 68%

68% — Before Louie

+15 Point Approval-Rate Improvement

At 100 deals/month, a 15-point approval-rate improvement means roughly 15 fewer mis-routed applications — reducing resubmission costs, lender relationship damage, and dead time in the deal log. (Simulation-based estimate — see /facts for methodology.)

Other Key AI Performance Metrics

Avg desk-to-done deal time (AI structured) 18.2 min (vs. 47 min industry)

Avg gross improvement per deal (AI structuring) +$312 / deal

BDC appointment set rate improvement (sim avg) +34% improvement

Simulation corpus coverage 0 runs · 0 scenarios

Why this moat cannot be purchased

A competitor starting today gets a blank model. They receive zero calibration from their first 10,000 deals. LouieAuto already has 0 calibrated scenarios baked into the weight matrix. The gap is 18+ months of floor-calibrated learning — and it widens every night the nightly reweight runs.

Network effect on acquisition

Each new rooftop an acquirer deploys to adds its deal outcomes to the shared model. At 100 rooftops, the model improves 100× faster than at 1 rooftop. The accuracy advantage widens as the install base grows — creating a structural barrier that new entrants cannot close with capital alone.

Acquisition Scenarios

Three acquirer profiles. Three distinct value unlocks.

The asset fits differently into each buyer's existing business — the value is highest for acquirers who already have distribution and need the AI layer.

Scenario A

Large Dealer Group (100+ Rooftops)

Deploy internally across the portfolio. Replace 6–12 point solutions per rooftop with a unified AI platform. Eliminate monthly SaaS fees and compound the lender routing moat at scale.

SaaS fees eliminated (100 rooftops)$480K–$960K/yr

Gross uplift (100 rooftops × +$312/deal × 100 deals/mo)+$3.1M/mo

BDC appointment improvement (34% lift)Meaningful volume

Lender approval-rate gain (+15 pts)15 deals/mo/rooftop

Model accuracy at 100 rooftopsCompounds nightly

Strategic upside: competitor groups do not have this. The AI advantage compounds year-over-year on a portfolio that doesn't.

Best Fit

Scenario B

Automotive Software Company (CRM / DMS Vendor)

Bolt the AI layer onto your existing install base. Instant 89-capability feature expansion. Convert the $24,995 perpetual license model into $299–$599/month SaaS — and charge back the delta as ARR on your existing book of business.

Feature expansion (immediate, at acquisition)89 capabilities

ARR at 10% legacy DMS attach ($299/mo)$5.4M/yr

ARR at 10% legacy DMS attach ($599/mo)$10.8M/yr

New sales motion requiredNone — existing reps

Churn defense uplift (dealers +$250K gross)Don't leave

Highest value path: existing distribution eliminates CAC. Each new dealer deployment compounds the lender model for all dealers on the platform.

Scenario C

Private Equity / Roll-up Vehicle

Deploy across a portfolio of acquired independents. Use AI-documented gross improvement as an EBITDA multiplier in future exit valuations. The $312/deal gross lift becomes a balance-sheet story, not just an operational story.

Gross lift per deal (AI structuring)+$312 / deal

At 10 rooftops × 100 deals/mo+$374K/yr gross

EBITDA multiple amplifier (4–6× auto)$1.8M–$2.7M uplift

Tech IP as diligence asset (exit)Differentiating

Compliance automation (FTC Safeguards)Risk reduction

The AI gross improvement is documentable, auditable, and traceable to individual deal records — making it defensible in a PE exit diligence process.

In all three scenarios, the acquirer captures value that is not available elsewhere in the market. No existing DMS vendor has a closed-loop lender routing model with 0 calibrated scenarios. No AI vendor has 18 months of floor-calibrated dealership data at this resolution. The window to acquire this at asset-replacement-cost pricing closes when a strategic buyer moves.

+$312

Gross/Deal (AI Struct.)

–63%

Desk Time Reduction

+34%

BDC Appt Rate Lift

$18M+

ARR Potential (5K Dlrs)

Deal Structure & Next Steps

A clean asset sale. 30-day close possible.

IP transfer only — no operational entanglement. The seller retains dealership operations. The acquirer receives the software, data, and 90-day transition support.

Asset Asking Price

Asking price

Replacement cost: $2.73M. First-mover data moat commands a premium. Full-source-code transfer included at closing.

Discussed under NDA

Contact to discuss

Replacement cost floor

18 months × 2 senior engineers + simulation compute + brand/domain. Hard cost to rebuild with no existing calibration.

$2,735,000

Replacement floor

Strategic premium justification

0-scenario AI corpus cannot be rebuilt — only grown. First-mover advantage in a $2.1B DMS market currently controlled by 1970s-era vendors. A large industry conglomerate paid ~$500M for AI marketing automation. LouieAuto's operational AI (lender routing, F&I, deal desk) represents acquisition at a fraction of the legacy AI vendor comp price — with deeper dealer floor intelligence.

+$0–$1.8M

Data moat premium

What Is and Is Not Included

✓ Full source code (173 files)

✓ All databases + simulation corpus

✓ Domain & brand (louieauto.com)

✓ Lender weight model (trained)

✓ 90-day transition support (seller)

✓ Architecture documentation

✗ Seller's dealership operations

✗ Customer relationships (none external)

Acquisition Process

1

Execute NDA

Mutual NDA required before financial data or source code inspection. Standard two-way NDA. 48-hour turnaround typically.

2

Diligence Package Delivered

Source code inspection, database schema, simulation corpus, architecture docs, API documentation, deployment guide. Full data room access within 5 business days of NDA execution.

3

Letter of Intent (LOI)

Non-binding LOI with price, structure, exclusivity period. Seller will respond within 3 business days. No auction process — first serious LOI with clean terms wins.

4

Confirmatory Diligence

Technical deep-dive with buyer's engineering team. Live walkthrough of the code. Simulation database inspection. 5–10 business days standard timeline.

5

Close — 30 Days from LOI

Asset purchase agreement executed. Code repo transferred. Databases and domain transferred. 90-day transition support begins. Clean close — no earn-out required given asset-only structure.

To Begin the Process

brian@louieauto.com

Include your organization name and a brief description of your acquisition thesis. NDA will be sent within 24 hours. All inquiries treated as confidential.

louieauto.com/acquire

Disclaimer: The scenarios on Slides 6 and 7 (Scenarios 1–3) are simulated outputs from the LouieAuto AI deal simulation engine across 81 modeled scenario templates. They are illustrative models, not real companies or live external customers, and no named dealership, person, or quote on those slides refers to a real entity. All gross improvement figures, ROI calculations, and operational metrics are simulation outputs. Performance in simulation deployments may differ. This document is confidential and intended solely for parties who have executed a non-disclosure agreement with LouieAuto. Unauthorized distribution is prohibited.