Hi-tech

EV Provider Reduces Dev Time by 50% with Cloud Optimization

Intelligent infrastructure for grid-free charging across thousands of locations

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100k+

Electronic vehicles charged.

2x

Reduction in development time by 10 hours per week.

30%

Less RAM consumption with cache optimization.

Client overview

An EV charging and energy management company delivers battery-integrated ultrafast chargers with onsite storage to ease grid constraints. Scalable systems speed deployment, cut infrastructure costs, and support electrified transportation for fleets, utilities, retailers, and public networks.

It partners with Fortune 100 companies, utilities, fleets, and fueling stations to launch reliable charging fast. Integrated energy management improves uptime and availability, while flexible deployment helps businesses enter the EV market without major grid upgrades.

Challenges

Distributed charging infrastructure had flaws in uptime control, location accuracy, and data processing across high-traffic environments.

Unreliable system

Service interruptions in billing and charging flow disrupted user experience, revealing the need for stronger uptime stability across the platform.

GPS inaccuracy

Signal fluctuations from devices created location mismatches, making it harder for users to find chargers and impacting field coordination efforts.

Data volume strain

Massive data generated by connected chargers strained backend systems, causing performance degradation during peak fleet activity.

Solution

We re-architected the EV charging platform to support scalable data ingestion, real-time visibility, and remote control across thousands of field-deployed chargers.

Fleet operations platform

Built a centralized platform to manage the fleet location, service health, charge scheduling, and energy used, providing real-time visibility and automated backend control at scale.

Real-time telemetry layer

Enabled charger-side telemetry to continuously stream device status, session details, and energy data, supporting diagnostics, reporting, and proactive service coordination.

Scalable data infrastructure

Implemented an event-driven backend to ingest millions of daily IoT signals from distributed chargers, ensuring consistent system stability and low latency during traffic spikes.

Remote device control

Enabled centralized control to reconfigure charging parameters, push software updates, and monitor health status remotely, reducing on-site intervention across global deployments.

Business impact

The new platform enabled efficient charging operations, reduced infrastructure load, and became scalable to serve growing demand with minimal overhead.

High-volume service delivery

The system reliably supported 100,000+ EV charge sessions with minimal downtime, ensuring performance across nationwide charging deployments.

Faster development velocity

Improved CI/CD pipelines and modular architecture cut engineering hours by 10 per week, enabling faster feature deployment and iteration cycles.

Lower infrastructure overhead

Resource optimization strategies reduced memory usage by 30%, improving system efficiency and reducing platform-scale operational costs.

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Hiren Dhaduk

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