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Case Study

Fleet Management

An AI-powered fleet management platform ensuring real-time tracking, data efficiency, and road safety through advanced technology and seamless scalability.

The Story

The platform utilizes cloud-based technology, machine learning, and AI to revolutionize fleet operations. It enhances performance and safety benchmarks by providing real-time insights, predictive analytics, and automated monitoring, ensuring fleets operate with maximum efficiency.

Our client is an advanced fleet management platform focused on road safety, using cutting-edge technology to provide real-time monitoring, improve driver safety, and enhance overall fleet efficiency.

Testimonial

Abhay Mathur

Head of Mobile Development

Challenges

  • > Delivering real-time vehicle data globally with near-zero latency.

  • > Tracking and updating vehicle geolocations accurately.

  • > Managing and processing large volumes of real-time data smoothly.

The Solution

The backend, built using Python and Django, stores data in a PostgreSQL database, ensuring efficiency. Confluent Kafka enables seamless processing of large data streams, while a modern React-based UI enhances user experience. The entire system is deployed on an AWS Kubernetes cluster, ensuring auto-scaling, load balancing, and uninterrupted performance.

The Outcome

The platform empowers transport companies and fleet managers with 360-degree fleet insights and an advanced Driver State Monitoring System. It enhances efficiency, safety, and operational control, ensuring optimized fleet and delivery performance from start to finish.

Contact

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