DealerOS AI

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  DMS Cards

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  Complete DMS Layout. Prototype.

DealerOS AI was inspired by more than 20 years of experience working inside automotive dealerships and supporting fixed operations. Dealership employees often use disconnected systems for service, inspections, parts, sales, customer communication, and reporting. These systems record what happened, but they rarely help employees decide what to do next.

I wanted to create a better DMS—one designed around modern dealership workflows, artificial intelligence, and the people who use it every day.

What DealerOS AI Does

DealerOS AI is a next-generation, AI-powered dealership management platform designed to connect:

Repair orders and service appointments Technician dispatching and digital inspections Photos, videos, measurements, and recommendations Advisor review and customer approvals Parts, sales, F&I, body shop, and accounting Customer and vehicle histories Reporting, audit trails, and role-based security AI-assisted recommendations requiring human approval

The initial product focuses on Service, MPVI, media documentation, customer approvals, and declined-service recovery because these workflows can produce measurable dealership value.

How I Built It

I began by mapping real dealership roles and workflows. I then designed a responsive web application with a relational database, authenticated APIs, rooftop-level data separation, employee permissions, audit logging, and persistent operational records.

The current prototype includes:

Repair-order creation and CSV importing Live service workflow management Technician inspection records Photo, video, audio, and document management Estimates and secure customer-approval links Individual approval and decline decisions Electronic signatures and timestamps Declined-service follow-up records Team and role administration Nationwide multi-rooftop support Automated production, migration, and security tests

AI functions are designed as decision support. They cannot independently diagnose vehicles, change prices, approve repairs, or contact customers without authorized employee review.

What I Learned

The most important lesson was that dealership software must connect actions—not merely display information. A useful system must understand how a technician’s inspection becomes an advisor recommendation, parts request, estimate, customer decision, completed repair, and future retention opportunity.

I also learned that trustworthy automotive AI requires:

Accurate source data Human approval Clear permissions Complete audit trails Secure customer information Explainable recommendations Measurable business results

A dealership ultimately measures software by its return:

ROI= Technology Cost Additional Gross Profit−Technology Cost ​

×100 Challenges

The largest challenge was translating an entire dealership into one connected data and workflow model without creating another complicated legacy system.

Other challenges included:

Supporting multiple rooftops and employee roles Protecting internal dealership information Separating customer-visible and internal media Creating secure, expiring approval links Preserving inspection and approval audit histories Designing for desktop, tablet, and technician phones Preparing for multiple DMS, OEM, payment, and communication providers

Live integrations require vendor contracts, authorized credentials, security reviews, and dealership participation. The current version therefore uses documented integration points and controlled workflows without pretending unavailable connections already exist.

What’s Next

The next milestone is a controlled pilot with dealership partners. The pilot will measure:

Inspection completion rates Advisor review time Customer approval rates Approved dollars per repair order Declined-service recovery Technician participation Customer engagement with inspection media

The long-term goal is straightforward: give dealerships one intelligent operating system that helps their employees work smarter, move faster, serve customers better, and generate more profit.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for DealerOS AI

Built With

• 5.6
• chatgpt
• codex
• sol
• work