From data to decisions: AI-powered predictive maintenance across 7 global accounts.

As Director of SaaS & IoT Telematics, the brief was to turn a stream of connected-vehicle data into something the field had never had: a warning before the breakdown. Fuel-injector failures were spiralling warranty costs and putting tier-1 accounts at risk.

95^%

Prediction accuracy

$50M⁺

Revenue influenced

25^%

Fewer field failures

99.95^%

Platform SLA

Global key accounts

$1.5M⁺

Cloud savings

The challenge

Failures the field could only see after the breakdown.

Customers were experiencing sudden fuel-injector failures mid-journey. Each one meant $500–$1,000 in warranty claims plus reputation damage — and there was no predictive signal. Failures were only detected after the vehicle had already stopped.

The revenue stakes were direct: key tier-1 supplier accounts were weighing a move to competitors. The data existed — fuel pressure, injector timing, engine load, all streaming off the telematics platform — but nothing was turning it into a decision.

The work

Engineer the signal, productize the prediction.

Built the ML model on real telematics data. Fuel pressure, injector timing and engine load — 50+ features engineered from raw IoT streams, with time-series preprocessing and scaling.
Trained to 95% accuracy. A gradient-boosted model reaching 95% true-positive rate (92% precision, 94% recall) on failure prediction.
Filed the IP. Patent #202141049000 on the predictive approach — one of four filings across the IoT / telematics domain.
Productized in-vehicle. A prediction API that alerts dealerships up to 100 miles before a likely failure — preventative maintenance instead of roadside recovery.
Held the platform. 99.95% SLA for 12+ months across the full device → cloud → mobile path, ISO 26262 compliant, with $1.5M in cloud-infrastructure savings.

“The data was already there. The work was turning it into a decision a dealership could act on — a hundred miles before the breakdown.”
— Swarup Kumar, on the BOSCH engagement

Outcomes

What it produced.

95% prediction accuracy — with a 25% reduction in field failures from early preventative maintenance.
$50M+ revenue influenced — the telematics platform became a multi-account revenue stream across 7 global key accounts.
99.95% uptime — held for 12+ months on a mission-critical IoT platform with full DR strategy.
Patent #202141049000 filed — part of a 4-patent portfolio that built a competitive moat.
$1.5M cloud savings — delivered while accounts renewed with expanded scopes.

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