Every objection a diligence team will raise — answered directly. Some answers are complete. Some are "not yet, and here's the plan." We built this deck because a straight answer is worth more than a polished non-answer.
The standard acquisition pitch leads with strengths and buries weaknesses in the data room. A diligence team finds the weaknesses anyway — and now they distrust the seller.
This deck does the opposite. Every slide starts with the objection as a diligence team would state it, then gives our answer. If we don't have a complete answer yet, we say so explicitly and tell you what we're building to address it.
Our working theory: a seller who pre-empts every hard question with honesty signals that the underlying asset is real. If we were hiding something, we wouldn't publish this.
Module count messaging, attribution methodology (public), CLAUDE.md documentation, BHPH workflow verification, admin security panel, security audit (auth hardening, SQL injection fix, N+1 deal query fix, connection pooling).
External pilot customer, independent AUP audit, SOC 2 Type II, public outcome feedback dashboard.
220 top-level modules is the verified count — all licensed and included, at varying maturity (live, DMS-activated, or in active build). Each of those 220 modules breaks down into multiple discrete capabilities (individual workflows, reports, and tools inside it), which is where the larger "900+ capabilities" figure comes from. 220 and 900+ are the same platform measured two ways — module-level and capability-level — not two competing claims. Both numbers are independently verifiable: every module and its capabilities are browsable, by name, at louieauto.com/modules →.
All 220 modules — and the 900+ capabilities inside them — are in the perpetual license from day one, at varying maturity — live, DMS-activated, or in active build (see /status). A diligence team can verify the module count, capability count, status, and build history via the data room, or independently by browsing the full module directory at /modules.
We observed +$312/unit. We attribute 65% to LouieAuto — the midpoint of a 50–80% range. The full methodology is public at louieauto.com/attribution →. Here's the short version:
| Scenario | Attribution | PVR/unit | Annual / rooftop |
|---|---|---|---|
| Conservative | 40% | $125 | $120K–$150K |
| Our published estimate | 65% | $203 | $180K–$250K |
| Metric-supported | 75% | $234 | $215K–$290K |
| Optimistic | 90% | $281 | $260K–$380K |
Public-facing materials cite a $180K–$274K band — the 65% base through the metric-supported (75%) upside. The 65% midpoint ($180K–$250K) is the planning anchor; $274K is the upside band, not a point estimate.
At the most conservative 40% scenario, the dealer ROI is still $120K–$150K against a $24,995 perpetual price — a 4.8–6.0× return. Attribution uncertainty changes the magnitude but not the value proposition. Fed rate cuts (−100bps in H2 2024) are the largest market factor we adjusted for.
Zero external paying customers. All 1,167+ deals, all PVR data, all approval rate data come from LouieAuto's own AI simulation engine. This is the single biggest risk in the entire diligence package, and we're not minimizing it.
18 months of data from our AI simulation engine. All 38 subprime API tests passing. Consistent daily operation, zero churn (because there are no external customers to churn).
External pilot dealer — 30–50 units/month independent, 50% discounted price, 90-day study, results published publicly under dealer's real name. Target: Q4 2026.
AUP audit — Agreed-upon procedures engagement on DMS data and ActivityLog methodology. Target: Q3 2026.
Until the pilot runs, you are buying on the strength of simulation data and the integrity of this methodology disclosure. We can't manufacture external data that doesn't exist yet. What we can do — and have done — is publish everything about what does exist.
You're right that a knowledge base can be replicated. What can't be replicated in 6 months is the outcome dataset.
The 3,059-row operator knowledge base. The lender matrix structure. The system prompt templates. With 2 senior operators and 6 months: possible.
1,167+ deals of simulation outcome data. Every deal routed through LouieAuto logs its result (funded / declined / rerouted). The system reweights lender routing nightly from deal outcomes. A competitor must run 12+ months of simulation deals before their routing accuracy approaches ours — and they'd need a live store to do it.
After 12 months at a dealer, you have 1,200+ deals of outcome data proprietary to that instance. That data compounds monthly. Competitors can copy the architecture; they can't fast-forward the calibration clock. The outcome feedback loop is the moat — not the spreadsheet.
No external sales team. No channel partners. No SDRs. This is a deliberate choice, not a failure.
Scaling before product-market fit confirmation (i.e., before external customers validate the simulation-modeled output against their own deal flow) creates channel conflict with potential acquirers and misaligns the valuation narrative. We are not in the growth phase — we are in the validation phase.
Founder runs sales conversations. Inbound inquiries exist. No commercial ARR booked. Two paid pilot conversations active. Deliberate decision to not scale before external validation exists.
An acquirer with an existing DMS book of 5,000–15,000 rooftops doesn't need a new sales team — they need an add-on module their reps already sell. That's the acquisition thesis: distribution, not origination.
Standalone sales scalability is a risk for a standalone business. For a strategic acquirer with an existing dealer base, the sales motion is already built — LouieAuto is an upsell, not a new category. If you're a PE buyer planning a standalone rollup, this is a genuine gap. If you're legacy DMS, legacy DMS providers, or the conglomerate, it's not.
We're compliant on the controls that matter for dealer operations today. SOC 2 Type II is the outstanding item — it's a process gap, not a security gap. Enterprise deals above $50K/year will need it; the timeline is 60–90 days from engagement start.
Fair concern. Here's the breakdown of what's tribal vs. encoded:
| Knowledge type | Location | Transfer risk |
|---|---|---|
| 42-lender rate matrix and routing logic | System prompts + lender_weight_cache DB table | Low |
| 3,059-row operator knowledge base | Structured DB rows, documented schema | Low |
| Desk-management decision trees | Encoded in AI system prompts (versioned) | Low |
| Lender relationship access | Founder's personal relationships | Medium |
| Prompt engineering judgment | Partially encoded; partially tribal | Medium |
| Floor instinct / edge case handling | Partially tribal | Medium |
90-day structured onboarding: Weeks 1–4 live shadowing every active deal workflow. Weeks 5–12 parallel desk coverage. Post-close consulting available at $350/hr. 12-week formal knowledge transfer plan in data room. Multi-year advisory available for enterprise acquirers. The medium-risk items are addressable; they're not blockers.
CSV-via-email is the current production path. The API architecture is built. The gap is partner agreements, not engineering.
CSV import via dealer email. DMS exports a daily P&L and inventory file; LouieAuto ingests it. Works on legacy DMS, legacy DMS providers, cloud DMS providers, legacy F&I software, legacy CRM software, legacy CRM software, and any DMS that can export CSV (all of them).
Limitation: same-day data rather than real-time. Sufficient for the daily-briefing and coaching modules; insufficient for live deal desk integration.
Full REST API layer exists in src/routes/ — 600 API routes total, 107 documented and visible in client-side code at /api-docs. Real-time DMS connection requires vendor API partner agreements (legacy DMS Partner Program, legacy DMS providers RCI, cloud DMS providers Developer Portal).
Acquirer advantage: legacy DMS, legacy DMS providers, the conglomerate, or any DMS acquirer with an existing partner agreement flips LouieAuto to real-time integration immediately post-close. No engineering work required — only agreement transfer.
The CSV path is a real limitation for standalone operations. It's not a limitation for a strategic acquirer who already has DMS API access. The integration value of this asset is disproportionately higher in acquirer hands than in standalone operation.
This is a software asset acquisition, not a revenue-multiple SaaS deal — there are zero real paying dealers today. The range is built from what it costs to replace the build, plus what a buyer with an existing dealer network could realistically ramp to in the first two years:
| Basis | Metric | Implied value |
|---|---|---|
| Build-cost replacement | 407K LOC · 900+ capabilities · 600 API routes · 18 months | $2.5M–$4M |
| Revenue at first 50 dealers | 50 × $24,995 one-time | $500K Year 1 |
| Revenue at 200 dealers (12-mo ramp) | 200 × $24,995 | $2M Year 2 |
| Acquisition thesis range | Buyer-type dependent | $1.5M–$5.5M |
Public M&A comps in this category (digital-retail and CRM/workflow overlays acquired by DMS-scale strategic buyers) were revenue-generating businesses at the time of acquisition, sold for hundreds of millions. LouieAuto has zero external ARR today — a revenue-multiple framing would overstate what's actually here. The honest comp is build-cost plus ramp, not a multiple of a number that doesn't exist yet.
$1.5M–$5.5M depending on buyer type — strategic acquirer with an existing dealer network (highest value, flip to 500+ stores immediately), founder/operator integration, platform consolidation, or a roll-up play. Full methodology and buyer-type breakdown at louieauto.com/for-investor →.
LouieAuto is a Node.js application with no proprietary infrastructure dependencies. Here's the actual deploy sequence:
Live system processing real deals in 48 hours. Full DMS integration requiring partner API agreements: 30–90 days depending on the acquirer's existing vendor agreements. The claim is accurate for the software deployment; it's not a claim about DMS data integration timeline.
At 85% gross margin, LLM inference is the primary variable cost. Here's what it actually looks like per store per month:
30–50 units/month. Daily briefings, lender routing, basic coaching. ~2M tokens/month.
75–120 units/month. All coaching modules active, voice BDC, nightly reweighting. ~5M tokens/month.
200+ units/month. All modules, heavy AI coaching, ambient floor mode. ~12M tokens/month.
At $24,995 perpetual pricing, a store generating $80/month in inference costs reaches payback in the first year of savings vs. legacy DMS alone — AI inference is effectively free relative to the value delivered. For an acquirer on subscription at $797/month, LLM cost is ~10% of revenue at typical usage — maintaining 75–80% gross margin. An acquirer with an existing Anthropic enterprise agreement pushes gross margin above 90%.
CFPB rulemaking on auto lending is a real industry risk — but it targets lenders, not routing software. LouieAuto is closer to a compliance aid than a compliance risk: helping dealers submit cleaner deals to appropriate lenders reduces adverse action rates, which is the CFPB's stated goal.
The $1.5M–$5.5M range is a software-asset valuation (build-cost plus revenue-ramp math), not a number that climbs on a validation schedule. The pilot and the AUP audit don't reprice the asset — they reduce a buyer's execution risk on the ramp assumptions already inside that range. The roadmap above is public so a diligence team can judge that risk directly. Full methodology at /for-investor.
Attribution is 40%. External pilot shows half the observed results. Sales ramp is slow. SOC 2 takes 6 more months. What does the acquirer still get?
220 modules. 900+ capabilities. 600 API routes. 1,200+ git commits. 407K lines of code. Clean Node.js stack. 18 months of simulation refinement. Deployable anywhere. No proprietary infrastructure lock. Standalone rebuild cost: $2.5M–$4M.
42-lender rate matrix. 1,167+ routed deals. Nightly reweighting engine. Bankruptcy Data Center pipeline. 3,059-row knowledge base. This data cannot be bought or scraped — it was built in a live dealership over 18 months.
$1.5M is the low end of the acquisition thesis range regardless of acquirer scale — the codebase, operator-encoded lender playbooks, stip logic, and desk-voice scripts have a documented build-cost floor independent of how the sales ramp plays out.
Even in the worst-case scenario — attribution wrong, pilot disappoints, sales slow — an acquirer still gets a fully functional AI dealer platform with $2.5M–$4M in rebuild cost, 1,167 simulated deal scenarios of CFPB-calibrated routing data, and a 42-lender matrix, at the $1.5M floor of the $1.5M–$5.5M range. That's still a compelling technical acquisition floor.
Same $1.5M–$5.5M range. Waiting doesn't buy a discount, and it doesn't create a premium either. The product keeps shipping — 2 modules every two weeks. SOC 2 gets done. The pilot data comes in. Those de-risk the ramp assumptions inside the range; they don't reprice the asset on a schedule.
Risk: a competitor or adjacent acquirer moves first and the asset is no longer available.
Same $1.5M–$5.5M range — and you control the validation process. Your pilot dealers. Your audit firm. Your SOC 2 timeline. Your DMS API agreement applied immediately.
Risk: external validation shows weaker results than the simulation-modeled output.
For a strategic acquirer with existing distribution: moving now is better. The product is deployable immediately to your dealer base; you don't need external validation — your first 10 deployments are your validation. For a financial buyer building a standalone: waiting for external validation reduces your execution risk without changing the price.
A structured checklist for the diligence team — what's verifiable today vs. what requires NDA access:
Verify today — no NDA
Verify under NDA
Some answers are complete. Some are "not yet." None are deflected or hidden in an appendix.
If you identified an objection we didn't cover, or found an answer that doesn't hold up, email directly. We'll add it to the next version of this deck and credit the question.