Catch failures before they strand a vehicle — OBD diagnostics, fault-code intelligence, driver-linked wear and availability planning. The vehicle told you four times. The trick is reading it before the fifth.
Using OBD/ECU data, fault-code history, usage patterns and AI to anticipate a failure before it becomes a breakdown — so downtime is planned into a workshop slot, not suffered on a highway. The vehicle is already broadcasting the warning; predictive maintenance is what reads it and names the part.
A breakdown alert tells you a vehicle has already failed. Preventing the next one needs the fault code routed to an owner, its recurrence counted, the fuel and thermal drift read alongside it, and the wear attributed to how it's driven. The signals are already in your logs — what's missing reads them together and says a name out loud.
A single rear-left wheel bearing logged a fault code four times before it failed on a highway. Follow it through six leaks — each one a signal that was already in the logs. The ledger keeps score.
The rear-left wheel bearing raises a code in week 1. It's logged. It reaches no one. It raises three more over ten weeks — logged, unrouted — then fails on NH48. A code with no owner is not a warning. · the protagonist
Four codes logged on the way up. The fifth was the roadside.
Code C1095 appears in five of ten weeks. Each time it's cleared and forgotten. A code that returns is not the same as a code that fires once — but nobody was counting. · same code, five times
Harsh braking and abrupt loads wear brakes, clutch and drivetrain faster than the schedule expects. A handful of drivers are buying breakdowns early — and the maintenance calendar can't see them. · wear per driver vs plan
Most of the fleet wears to plan. The amber ones fail early — attributable to how they're driven.
Fuel-trim drift sits just under its alert line. Coolant drift sits just under its own. Neither trips an alarm alone — but read together they've been describing the same failing part for weeks. · two signals, one fault
Each under its own line. Correlated, they cross it.
When the bearing finally goes, the truck is down 60 hours — and 46 of them are the part in transit, not the repair. Predicted three weeks out, the part would have been on the shelf. · down for the part
The repair was never the problem. The waiting was.
Without a per-model health baseline, a score of 71 means nothing — there's no healthy line to have fallen from. Drift can't register as decline when there's no benchmark to measure it against. · nothing to fall from
The dashed ring is the baseline that was never set — so 71 has nothing to mean.
A breakdown alert tells you it failed — the ₹20 lakh you notice on the hard shoulder. The other ₹48 lakh is signals already sitting in your logs: codes with no owner, recurrence no one summed, fuel and thermal drift no one read together. The signals are already there. What's missing reads them together and says a name out loud — "rear-left wheel bearing, three weeks out."
The recovery is split by the product that earns it — so you can decide what to deploy first.
Vehicle Intelligence carries the page — it reads the signals the vehicle already broadcasts. Driver Behaviour attributes the wear; Asset Intelligence plans the availability. Fuel Monitoring lends its drift signal to the cross-signal read.
The engine of predictive maintenance: fault codes routed to an owner, recurrence counted, health scored against a per-model baseline, and a cross-signal read that links fuel and thermal drift to the fault they've been jointly describing. It turns a log full of noise into a named part, three weeks out.
Attributes wear to how a vehicle is driven — the harsh braking and abrupt loads that buy breakdowns early — so the pattern can be coached and component life extended.
Turns a predicted failure into a planned one — the part on the shelf, the workshop slot booked, the availability protected. Downtime scheduled instead of suffered.
Each product you add doesn't just catch its own signal — it sharpens the read below it, because it removes another reason a failure could hide.
Fault codes routed and counted, health scored against a baseline, fuel and thermal drift read together. The failing part becomes visible weeks before it strands anyone.
Link accelerated wear to the driving that caused it. A failure stops being bad luck and becomes a coachable pattern — the breakdown you prevent, not just predict.
Rank predicted failures by cost and criticality, stage the part, book the slot. The prediction becomes a plan — and the 46 hours of parts-wait disappear.
Predictive maintenance is a programme with a sequence — and the sequence matters, because each phase makes the next one readable.
Devices across the fleet, fault codes flowing to a named owner. The unrouted-code leak closes on day one — a code with an owner is a warning.
Per-model health baselines make drift mean something, and behaviour data attributes accelerated wear to the driving behind it.
Predicted failures ranked, parts staged, slots booked. The prediction becomes a plan — and parts-wait leaves the downtime cycle.
Predictive maintenance uses OBD/ECU data, fault-code history, usage patterns and AI to anticipate a failure before it becomes a breakdown — so downtime is planned into a workshop slot, not suffered on a highway. It reads the signals a vehicle is already broadcasting and names the part about to fail.
OBD/ECU data carries fault codes, recurrence and cross-signal drift — the evidence a failure is coming. Routing those codes to an owner, counting recurrence, and reading fuel and thermal drift alongside them turns a future roadside breakdown into a planned repair. The signals are already logged; OBD is what reads them together.
Yes. Harsh braking, over-revving and abrupt loads accelerate wear on brakes, clutch, tyres and drivetrain — buying breakdowns earlier than the maintenance schedule expects. Attributing wear to driving style lets you coach the pattern and extend component life.
Vehicle Intelligence (OBD) surfaces fault codes, recurrence, health scoring and cross-signal reads. Driver Behaviour attributes wear from misuse. Asset Intelligence plans availability and parts. Fuel Monitoring adds the fuel-drift signal to a cross-signal read. Together they turn suffered downtime into planned downtime.
