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case studies

Our client, a leading USA-based global automotive manufacturer ranking among the top three in the industry, specializes in offering a wide range of vehicles, including light, medium, and heavy trucks, buses, coaches, and bus chassis. With diverse warranty offerings tailored to different conditions, the client sought to gain deeper insights into their customer base and vehicle usage patterns.
In collaboration with the client, we developed a Proof of Concept (POC) solution aimed at analyzing truck route patterns to provide valuable insights. Our solution enabled the client to identify opportunities for the integration of electric or autonomous trucks, along with suitable electric charging station locations. Leveraging custom algorithms, we aggregated and filtered data from onboard telematics devices, merged it with external data sources such as electric charging station locations, and visualized key findings through an intuitive dashboard.
The primary challenge was to provide the client with a comprehensive understanding of how their customers utilize their vehicles. With vast amounts of data available from standard onboard telematics devices, our task was to extract actionable insights quickly to support management decision-making. Through rapid prototyping and agile development, we successfully demonstrated the feasibility of selected hypotheses, earning management approval for further initiatives.
Used Tech Stack: Python PySpark Azure Data Explorer Azure Databricks Tableau

Data Analytics & POCs for Top 3 Automotive Manufacturer

Our client is a leading IT product/IOT company based in Germany, known for its innovative technology solutions and expertise in the field.
We collaborated with our client to implement a robust traffic surveillance system using advanced video camera technology. The system was designed to detect various objects, including cars, trucks, bikes, and pedestrians, while also capturing their speeds and directions. This solution enabled real-time monitoring of traffic, significantly enhancing safety measures and providing valuable data for traffic analysis and planning. The successful implementation of the traffic surveillance system marked a significant milestone in our client's efforts to leverage technology for improving transportation systems.
One of the key challenges we encountered was managing and delivering six separate projects with varying complexities and requirements. Despite this, our team rose to the occasion, effectively tackling each project and ensuring successful outcomes. As a result, our client experienced notable achievements, including improved operational efficiency and enhanced customer experience across their product portfolio. The successful integration of the chatbot platform with various platforms such as Google Dialogflow, Alexa, Magento, and WordPress expanded the company's reach and enabled seamless communication with customers.
Used Tech Stack: Dialogflow, Alexa, Angular 2.x, Node.js, Express, C++, Python, Swift, PostgreSQL, MongoDB, Firebase, OpenCV

Traffic Surveillance System

Our client is a global technology, defense, and engineering group with a diverse portfolio of businesses spanning aerospace, smart city development, defense, and public security segments. With a focus on innovation and advanced technology solutions, they sought to develop a comprehensive maritime simulator and training engine to enhance training programs and operational efficiency.
In response to the client's requirements, we developed a cutting-edge training simulator with a 3D Maritime Visualization Engine. This engine included 5,000 square kilometers of land and sea terrain, approximately 200 modeled objects, real-world weather simulation, physics modeling, and day and night time logic. Integration with actual field devices enabled realistic visualization of various scenarios, including city architecture, natural elements, ocean conditions, harbors, and human modeling. The result was a sophisticated training platform capable of simulating diverse maritime scenarios with high fidelity and accuracy.
The primary challenge for the client was the need for a maritime simulator training engine based on a comprehensive visualization engine. This engine was essential for developing various tools for real-life data visualization and its application in training simulations, including piloting tankers and cargo ships. Despite this challenge, our team successfully automated training courses for unmanned surface vessels, enabled remote piloting of cargo and tanker ships and provided real-life port situation visualization capabilities. These achievements significantly enhanced the client's training programs and operational capabilities in maritime environments.
Used Tech Stack: C#, C++, Unity3D, Blender 3D, Adobe Photoshop & Illustrator