AI agents: Auto and logistics

Which ready AI agents exist in “Auto and logistics”

Auto and logistics

13 released templates. Each passed a check on test data; it is switched on in the panel by the director, and a person decides on every proposal. Example results are illustrative: the names and companies in them are made up.

Service reminders

The problem it removes: Customers forget about scheduled maintenance.

More detail

What it does: Reminders based on mileage and time.

What a person decides: The text.

For whom: Customer.

How to measure: Service bookings.

Example result: “Hi Yerlan! Per our records, your Camry has done about 15,000 km since its last service — right when the next one is due per the schedule. We have openings Wednesday at 10:00 and Saturday at 9:00; the service takes about 2 hours. Shall I book you?”

Repair status

The problem it removes: Customers call to check on their car.

More detail

What it does: Gives the customer the repair status.

What a person decides: The final decision on the outcome.

For whom: Customer.

How to measure: Repair status calls.

Example result: “Your car is in the paint shop — the second coat is drying. It'll be ready Friday by 17:00, and we'll message you as soon as it's ready for pickup. If Saturday is more convenient, that works too — the shop is open until 15:00.”

Shipment status

The problem it removes: Customers don't know where their shipment is.

More detail

What it does: Shipment status and delivery times.

What a person decides: The final decision on the outcome.

For whom: Customer.

How to measure: Shipment status calls.

Example result: “Your shipment is in Karaganda now and will reach Astana tomorrow by 12:00. The driver will call an hour before arrival — please have a power of attorney ready for receiving the goods if someone other than the director will accept them.”

Shipping quote

The problem it removes: Shipping costs are calculated by hand.

More detail

What it does: Calculates from the company's rates.

What a person decides: Exceptions.

For whom: Sales rep.

How to measure: Time per quote.

Shipping documents

The problem it removes: Cargo documents get lost.

More detail

What it does: A checklist and document collection.

What a person decides: Sending.

For whom: Staff member.

How to measure: Runs delayed by documents.

Example result: “Situation: Almaty — Astana run on October 9, 18 pallets. In hand: carriage contract, invoice, product certificate. Missing: the waybill (issued by the shipper's warehouse) and driver Akhmetov's power of attorney — it expired October 5. Key point: without the POA, the driver won't be allowed to load. Options: 1) a new POA today — needs the director's signature; 2) switch drivers — Serikov's POA is valid. Recommendation: 2, if the director isn't in by 15:00. Today: request the waybill from the warehouse.”

Inspection results in plain words

The problem it removes: The customer doesn’t understand the inspection sheet and turns down needed repairs — or agrees to everything and gets angry later.

More detail

What it does: Explains the technician’s inspection sheet: what was found, what needs doing now, what can wait, and what it costs — and asks the customer to approve the work.

What a person decides: Approving the work and the final price.

For whom: Customer.

How to measure: Work approved after inspection.

Special-order parts

The problem it removes: The part isn’t in stock — the customer goes to another shop before getting an answer.

More detail

What it does: Tells customers when a special-order part will arrive, whether prepayment is needed, OEM or aftermarket, and how to book installation — per shop rules.

What a person decides: Ordering from the supplier.

For whom: Customer.

How to measure: Part orders that became repairs.

Example result: “Arman, an OEM control arm for your Tucson takes 3–5 business days to order; an aftermarket one arrives tomorrow. We need a 50% deposit to order, the rest after installation. As soon as the part arrives, we’ll message you and book a time that works — installation takes about an hour.”

Seasonal tire changes

The problem it removes: Every fall and spring, everyone writes at once: how much for a tire change, and when’s there an opening?

More detail

What it does: Answers customers about seasonal tire changes: price by rim size, what’s included, how long it takes, tire storage, and how to book — per the tire shop price list.

What a person decides: Off-schedule bookings and discounts.

For whom: Customer.

How to measure: Tire change bookings from chat.

Vehicle pickup: what was done

The problem it removes: At pickup the customer hears “all done,” and a week later calls to ask what was replaced and what the warranty is.

More detail

What it does: Writes the customer at pickup from the repair order: work done, parts installed, labor warranty, and when the next service is due.

What a person decides: Final amount and warranty terms.

For whom: Customer.

How to measure: Follow-up “what did you replace?” calls.

Example result: “Samat, your car is ready. Work done: oil and filter change, front pads and rotors — Brembo parts. Labor warranty: 6 months or 10,000 km. The technician recommends rechecking the lug nut torque after 2,000 km. Next service is due at 75,000 km. You can pick it up until 20:00.”

Weekly service bay load

The problem it removes: One day the lifts sit idle, the next day customers get turned away — booking is done however it happens.

More detail

What it does: Shows bay and technician load from the week’s bookings: open slots, overloads, who to offer a reschedule, and where to fit urgent repairs.

What a person decides: Rescheduling and technician schedules.

For whom: Service advisor, manager.

How to measure: Idle bays; customers turned away.

Example result: “Action: lighten Wednesday — bay 2 has 11 hours booked in a 9-hour day; offer to move the suspension job to Thursday, when bay 2 has 6 open hours. Put this week’s urgent work on Tuesday afternoon, when both bays have openings. Impact: nobody waits for their car until late at night. Risk: the customer may say no — then bay 1 on Wednesday after 15:00. Fallback: keep the booking on Wednesday.”

Auto shop week: revenue and technicians

The problem it removes: The shop owner sees only the cash total and doesn’t know which jobs and technicians bring in the money.

More detail

What it does: Shows revenue by job type and technician from the week’s repair orders, plus comebacks and what to decide.

What a person decides: Prices, bonuses, and decisions about technicians.

For whom: Owner.

How to measure: Comebacks; revenue per technician.

Oil and consumables: what fits

The problem it removes: “Which oil does my car take, and how much is an oil change?” — every day, and every time someone digs through a spreadsheet.

More detail

What it does: Uses the shop’s chart to tell customers which oil fits their car, how many liters it needs, what the change costs with labor, and how to book.

What a person decides: Switching to a different oil at the customer’s request.

For whom: Customer.

How to measure: Oil change bookings.

Cars in stock and test drives

The problem it removes: Dozens of people message about Kolesa.kz listings, and while someone looks for an answer, the buyer drives to another dealer.

More detail

What it does: Tells buyers whether there’s a car that fits their request — year, mileage, drivetrain, price — whether financing or trade-in is possible, and when to come see it and test-drive — from the dealer’s inventory list.

What a person decides: Price, negotiation, and financing terms.

For whom: Buyer.

How to measure: Viewings and test drives from chat.

Basis: product documentation; the platform code. This page describes what exists in this build, not what is planned.

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