intuService · AI Service Advisor
An AI service advisor for auto and fleet service networks. It answers the phone, works out what is actually wrong with the vehicle, and books it into the right bay with the right parts and the right labour time. You pay when the repair order closes.
A booking system stops at step one. The value is in the middle three.
The problem
The advisor qualified to triage the call is the same person standing at the counter with a customer in front of them. The phone slips exactly when demand is highest.
25–40%
of calls missed at the average independent repair shop
Famulor, 202686%
of callers who reach voicemail never leave a message
Forbes, 202547%
of calls missed where a technician answers the phone
BIA Advisory Services, 202565%
technician billable efficiency — idle bays are the real cost
WifiTalents, 2026Why generic agents fail here
Capturing make, model, year, mileage and VIN is a structured intake form read aloud. It does not decide how long the job takes, which bay it needs, or whether the parts are on the shelf — which is where the scheduling error, and the cost, actually originate.
“There's a grinding noise when I brake”
must become
Pad wear against rotor against caliper — narrowed by symptom detail, mileage and service history.
How long the inspection realistically takes on this vehicle, not what the guide says.
Checked against live local stock before anything is promised to the caller.
Correct lift type and a technician whose skills match the likely work.
A slot sized to the real job, so the schedule holds for the rest of the day.
Whether the vehicle should be driven in at all, or needs recovery.
The triage model is built on twenty years of direct automotive industry experience in the founding team — how symptoms map to faults in practice rather than in a manual, where labour guides diverge from real bay time, and where the upsell boundary sits between service and pressure.
How it works
Sub-second turns
Natural conversation in English and Spanish with interruption handling and graceful degradation on poor mobile lines. Callers are told they are speaking to an AI advisor.
The defensible part
Symptom to probable fault to diagnostic time to parts dependency to labour allocation — an encoded automotive service knowledge base combined with the shop's own historical work-order data.
SMS & DMS write-back
Integrates with shop management and dealer management systems for live parts availability, bay and lift capacity, technician rosters and labour guides. Writes the booking and opens the repair order.
Handoff & compliance
Clean human escalation with the full conversation transcript, state-by-state call recording consent, TCPA-aware outbound, and a SOC 2 readiness track.
Pilot
These are the targets we commit to before the pilot starts. They are commitments, not results — we publish them up front so there is something concrete to hold us to.
| Measure | Typical baseline | Pilot target |
|---|---|---|
| Call answer rate | 60–75% | ≥ 98% |
| After-hours calls captured | ~0% | 100% |
| Triage accuracy — fault category and labour bucket | — | ≥ 85% |
| Booking conversion on answered calls | — | ≥ 35% |
| No-show rate | your baseline | − 20% |
| Escalation to a human | — | ≤ 20% |
| Median turn latency | — | < 800 ms |
| Spanish-language call handling | — | ≥ 90% accuracy |
Thirty days of measurement on your existing call data before we go live. Without it there is no honest attribution, and outcome pricing has nothing to stand on. It protects you more than it protects us.
Start here
Tell us how many locations you run and which shop management system you use. We will come back with a scoped pilot and a baseline plan.