Not a demo asset. An operator's tool.
LouieAuto is used every business day in the operator's own stores — built by a car guy who ran it where he works before ever offering it to anyone else. Real numbers, real stores, verifiable results.
Before / After — Founder's Pilot Group
Before Louie
After Louie
Structural facts.
Each number below is structurally verifiable. Where a live endpoint exists we link it.
Footnote: "operator deployment" refers to the operator's dealer group. This is not a third-party paying customer reference — it is a working product with an in-house reference site, four quarters of operating history.
The /api/moat/public endpoint pulls from commodity sources — FRED, EIA, UMich,
OEM program feeds. The moat is not the data. The moat is the operator-encoded system prompts,
lender playbooks, stip logic, and desk-voice scripts that sit between those inputs and the dealer.
"A competitor can call the same APIs. They cannot replicate 30 years of floor experience compressed into prompt engineering — without hiring an operator and spending 18–24 months encoding the institutional knowledge. That encoding is what ships with the asset."
The moat compounds. Beyond the encoded knowledge, every deal that flows through Louie gets logged with its outcome — funded or declined, trade auction price vs. estimate, structure that held vs. structure that got recut. After 12 months of production use, the system has a store-specific outcome record that compounds continuously. The longer it runs, the sharper the routing — trained on real dealership outcomes at real current-market conditions, at that store, with that lender mix.
Your deal data never trains a public AI model. LouieAuto uses Anthropic's Claude API with zero-data-retention settings — deal records are passed as context, not stored by the model provider. Your outcome history compounds on your instance only.
- ✓ Dealer data stored in self-contained SQLite on your server — no shared cloud database
- ✓ Full data portability — your outcome dataset exports as JSONL on request, usable with any AI stack
- ✓ One-page Data Processing Agreement available — CDK and Reynolds do not offer equivalent dealer-favorable DPAs
- ✓ FTC Safeguards Rule compliant at the control level — access log, encryption at rest, breach notification workflow all documented
Founder's pilot group — what moved.
Operator-controlled pre/post study across a multi-store franchise dealer group — a mix of domestic and import franchises. Before/after metrics below are rolling 12-month trailing vs. the 12-month trailing window before LouieAuto was deployed across the group. Store names are withheld from the public write-up.
Method: metrics pulled from the group's DMS monthly P&L rollups and internal ActivityLog event tables. Windows compared: pre-deployment (Feb 2024–Jan 2025) vs. current (Mar 2025–May 2026). No store was excluded. Group benefits from a mature operator team independent of LouieAuto — the uplift is LouieAuto's contribution on top of an already-competent operating baseline, not a greenfield turnaround.
How counted: ActivityLog events
lender_submit → lender_approved within 24h on the same deal ID. Cohort: our dealerships · ~1,167 retail deals across the measurement window.Measurement window: Pre (Feb 2024–Jan 2025) vs. Post (Mar 2025–May 2026). No stores excluded.
Industry benchmark: AFSA data puts franchise dealer first-look at 62–71%. Our pre-deployment baseline was 68% — in line with industry. Post-deployment: 83%.
How counted: DMS monthly P&L export (Gross by RO) averaged across our store group, trailing 12 months per window. The $312 is the full observed delta; at 65% attribution the figure attributable to LouieAuto is $203/unit.
Validation: Correlated against Next-Actions AI commit rate per deal — months with higher AI engagement showed consistent PVR correlation, supporting attribution model.
lead_created event to first logged outbound contact attempt (call or SMS).The 52-second figure: Median auto-fire time from the 60-Second Lead Responder. Manual BDC override still averages ~8 min; 52s is the as-fired auto-response median across enabled leads.
Downstream impact: Lead-to-appointment rate lifted +8.4 points blended (trailing 12, Facebook Marketplace + phone-in rollup). Attribution window: appointment booked within 7 days of first contact.
How counted:
InventoryCurrent.days_in_stock ≥ 60 as % of total units on hand, per store, per month-end.Dollar impact: Floor plan avg $28/unit/day × ~88 fewer aged units group-wide × 365 days = ~$900K gross floor plan exposure eliminated. Conservatively modeled at $340K net of wholesale disposal friction. Per-rooftop figure: ~$68K/yr at conservative midpoint.
What these numbers mean for your store
The metrics above are the reason the $150K–$274K/rooftop/year uplift claim is grounded in reality. It's the pilot group's own result, broken down by the specific module that drove it, across a controlled multi-store operating window. A dealer deploying LouieAuto should expect a range around this band, subject to starting PVR and inventory discipline.
What is not claimed here.
LouieAuto is pre-commercial — the founder's five-rooftop group is the reference site, with 18 months of live production data before external licensing. Pricing is live and inbound inquiries are active. The value math on /facts reflects actual operating results from that reference group, not projected figures.
Everything on this page is either structurally verifiable (store count, years in production, module count, DB rows) or live-endpoint-auditable (moat refresh, uptime).
Want to see the full platform?
The live demo runs every module shown on this page — real data, real deal math, no slides.
brian@louieauto.com · Questions answered same business day