AI in automotive, built for the service drive and the parts counter
Custom AI for service scheduling, parts, warranty, and lead handling, integrated with your DMS. Fixed project cost, 4 to 12 weeks, and your team owns the code.
How it works
Fixed operations carry the dealership, and they run on decisions made under time pressure: which appointment fits which technician, which part to stock before the RO is even written, whether a warranty claim will survive the OEM audit. Those decisions live across a DMS, a scheduler, a parts catalog, and an OEM portal that were never designed to talk to each other. APPIT builds custom AI software that reads all of them, does the routine reasoning, and gives service advisors, parts managers, and BDC staff a decision instead of a data-entry task.
Service scheduling that fills bays instead of a calendar grid
Appointments are booked against real capacity, technician skill, and parts availability, then confirmed and rescheduled without an advisor picking up the phone.
- Capacity-aware booking by bay, technician certification, and job duration
- Open recall and declined-work campaigns run against your service database
- SMS and voice confirmations, reminders, and self-serve reschedules
- Appointments written back to the DMS and shop scheduler in real time
Parts stocked to the work that's actually coming
Parts demand is forecast from open repair orders, local VIN mix, and campaign volume, so the counter has the part before the vehicle arrives and less capital sits on the shelf.
- Demand forecasting from open ROs, VIN parc, and recall activity
- Obsolescence and return-to-manufacturer windows flagged before they close
- Automatic supersession and alternate-part matching across catalogs
- Stocking guides tuned per location for multi-rooftop groups
Warranty claims assembled and validated before submission
Claim packets are built from repair order notes, labor operations, and parts records, then checked against OEM rules so rejections and chargebacks stop arriving weeks later.
- Story, cause, and correction drafted from technician notes for review
- Labor operation and time allowance matched to the documented repair
- Pre-submission validation against OEM policy and documentation rules
- Audit trail retained per claim for OEM review and internal reporting
Where teams use it
Built for real revenue work.
After-hours lead handling and trade-in quoting
Most inbound sales inquiries arrive outside staffed hours and go cold by morning. An inventory-aware assistant answers by phone, chat, and form around the clock, gives a defensible trade-in range from VIN, mileage, and photos, and books the appointment with the full transcript handed to the CRM.
Recall and declined-work outreach for a dealer group
Thousands of open recalls and previously declined repairs sat unworked because no one had time to call through the list. Targeted outreach now runs continuously across twelve rooftops, prioritized by revenue and bay availability, and books directly into open capacity.
Warranty claim preparation for a franchise service department
Two administrators spent their week rewriting technician notes into acceptable claim language and chasing missing documentation. Claims are now drafted and validated automatically, with the administrators reviewing exceptions instead of authoring every packet from scratch.
“The warranty backlog used to be measured in weeks and we were writing off rejected claims every month. Now claims go out the same day the repair order closes and our first-pass acceptance is the highest in our OEM region.”
FAQ
Questions, answered.
How is AI being used in the automotive industry right now?
Outside of the vehicle itself, the practical wins are in fixed operations and lead handling: forecasting parts demand, scheduling service against real shop capacity, drafting and validating warranty claims, and answering inbound inquiries within seconds at any hour. These are bounded problems with clear success metrics, which is why they tend to pay back within a quarter rather than requiring a multi-year data program.
Will this integrate with our DMS?
Yes, and it is usually the first thing we scope. We work with CDK, Reynolds and Reynolds, Tekion, Dealertrack, and PBS, alongside scheduling tools, parts catalogs, and OEM portals. Where a vendor restricts API access we use certified integration partners or scheduled data exchange, and we confirm the integration path in writing before the project is priced.
Does this replace our BDC or service advisors?
It removes the repetitive volume they never had time for, such as after-hours inquiries, reminder calls, recall lists, and claim paperwork. Advisors and BDC staff keep the conversations that need judgment, and they walk into them with the vehicle history, inventory position, and prior contact already summarized. Most groups redeploy the recovered hours into outbound work rather than reducing headcount.
What does an automotive AI build cost and how long does it take?
A single-rooftop or single-workflow project such as service scheduling or warranty claim preparation typically runs $50,000 to $110,000 and delivers in 5 to 8 weeks. Group-wide programs covering parts, service, and lead handling generally take 10 to 12 weeks. Pricing is fixed at scope sign-off, the team is named, and all code and models transfer to you at handover.
Keep exploring
More from the Leadify platform.
Custom AI Software
Production AI built around your systems, delivered at a fixed cost with full code ownership.
AI Automation
Warranty packets, repair order notes, and parts paperwork processed without manual re-keying.
Automotive CRM: 10,000 leads
The sales-side playbook for dealer groups managing lead volume at scale.
Fix the bottleneck in your fixed ops
Tell us where the hours are going, from the service drive to the warranty desk, and we'll return a scope, a fixed price, and a date.