The best predictive maintenance software for a fleet is the one that turns the telematics data it already collects into repairs its service shop can schedule, and proves that on the fleet’s own vehicles before a contract is signed. Feature lists rarely show this. Six checks do, and each one can be tested in a demo or a one-week evaluation. Each check below comes with a worked example from Tensor Planet, so there is a concrete answer to hold every vendor against.
Check 1: It works on the data you already have
Predictive maintenance built on AI for fleets runs on two inputs: the telematics feed from your vehicles and the repair history in your maintenance system. Software that needs new sensors or gateways adds install time, vehicle downtime and a second data source to reconcile. Ask which telematics and maintenance platforms the vendor reads today, and whether access is read-only.
Worked example: Tensor Planet reads Samsara, Geotab, Motive and Verizon Connect telematics, plus RTA Fleet, Whip Around and Fleetio maintenance data, among others, through API connections. Nothing is installed on the vehicles.
Check 2: Each alert says what to fix
A fault code tells a technician a value is out of range. It does not say which component is failing, why, or what to do next, so the diagnosis still happens in the service bay. Ask to see a real alert from a live customer. It should name the component, the likely cause and the recommended repair.
Worked example: every Tensor Planet breakdown alert carries a diagnosis and a recommendation, such as a DPF that needs cleaning before soot load forces a derate. The technician starts with the answer instead of the search.
Check 3: The timing is early enough to plan
Earliest is not the goal. An alert six months out gets ignored, and one the day before ends in a tow. Good maintenance software, powered by AI, learns what normal looks like for each vehicle from its own load, duty cycle, idle time and operating heat. It watches for drift from that baseline and flags a component when failure is close enough to act on with confidence. Ask how far ahead alerts usually land, and how many were acted on.
Worked example: Tensor Planet detects and diagnoses failures two to three weeks ahead, which leaves time to order parts and book the bay. Brakebush Transportation, Inc. acted on 9 alerts in its first seven weeks.
Check 4: It fits how your service shop already works
An alert that lives in a separate dashboard depends on someone remembering to open it. Ask whether alerts arrive as work orders in the maintenance system your technicians already use, and whether repairs can be timed around scheduled PM visits.
Worked example: Tensor Planet pushes each alert and its recommendation into the existing maintenance system as a work order, so technicians work from their normal queue.
Check 5: Results come with a name and a time window
A percentage with no time window is hard to check, and so is a dollar figure with no fleet behind it. Ask for named customers, the number of vehicles, the period measured and what was counted. Then ask to speak with one of those customers directly.
Worked example: Troiano Waste Services saw 41% fewer exhaust-related repairs in its first 10 weeks, on 55 vehicles. Brakebush Transportation, Inc. saved $26,517 and 142 downtime hours in its first seven weeks, on 110 tractors.
Check 6: You can test it on your own vehicles first
A demo on sample data shows the interface. A test on your own fleet shows whether the models find real problems in your vehicles. Ask for a short evaluation on your own data that ends with a list of at-risk vehicles. Each vehicle on the list should carry the component at risk, the timing and the cost of waiting, so your technicians can check the results against what they already know.
Worked example: Tensor Planet’s free fleet diagnostic does this in one week, read-only, with no change to your service shop.
Questions fleets ask
How do you test predictive maintenance software on your own fleet data before you buy?
Tensor Planet runs a free fleet diagnostic on your own vehicles. It connects read-only to your telematics feed and six months of work orders, reconciles the two, and within one week returns your at-risk vehicle list with next-month and next-year savings in your own numbers, plus a 30-minute walkthrough. Nothing is installed on the vehicles.
Which predictive maintenance software covers all makes and models in a mixed fleet?
Tensor Planet works across vehicles of all makes and models, light, medium and heavy-duty, because it reads the telematics feed a mixed fleet already runs. It detects, diagnoses and prevents failures in DPF, DEF, EGR, NOx, coolant and battery systems, plus many other systems. Brakebush Transportation, Inc. saved $26,517 and 142 downtime hours in its first seven weeks.