Cognizant Mobility

Getting data out of a truck is one thing. Building a useful service around it is another. A connected service works with one vehicle configuration. What does it take to support different truck brands, software versions and data interfaces? Scaling connected services means: ▪️ Giving vehicle data consistent meaning across configurations and software versions. ▪️ Managing interfaces and compatibility so updates don’t break existing services. ▪️ Designing applications around the decisions fleet managers, drivers and service teams need to make. At Cognizant Mobility, we bring together vehicle software, connected platforms, cloud engineering, data platforms and UX to address these challenges across the full system. The goal: less custom integration for each additional vehicle variant, more reusable service functionality and information people can act on. Reliable data and vehicle context also lay the groundwork for fleet analytics and AI. What is the biggest obstacle to scaling your connected services across vehicle variants? Visual created with AI assistance. #ConnectedVehicles #CommercialVehicles #CloudEngineering #DigitalEngineering #CognizantMobility

The truck hasn’t stopped. Can your AI already see why it might? An unusual temperature trend may signal a developing fault – or simply reflect a heavier load, a steep route or changing weather. The difference matters. Miss a relevant warning and a vehicle may break down. Flag every deviation and service teams lose trust. Making fleet intelligence useful means: ▪️ Interpreting telemetry in the context of vehicle configuration, operating conditions and maintenance history. ▪️ Validating models against real outcomes, including missed faults and false alarms. ▪️ Turning findings into clear information that helps service teams decide what to inspect, when and why. ML can help detect patterns and estimate failure risk. GenAI can help service teams find relevant diagnostic procedures and technical information. Both need reliable data, validation and engineering judgment. At Cognizant Mobility, we combine vehicle expertise, data engineering and AI & analytics to connect these capabilities with practical fleet and service workflows. The goal: earlier intervention, better-informed maintenance and fewer avoidable disruptions. What is the hardest part of turning vehicle data into reliable maintenance recommendations? Visual created with AI assistance. #FleetAnalytics #PredictiveMaintenance #ArtificialIntelligence #CommercialVehicles #CognizantMobility

AI is everywhere. Where’s the business impact? Join us at Munich’s Allianz Arena on October 8 to explore the decisions that turn AI potential into measurable results – with experts from industry, cloud and engineering. The AI-Driven Game: Winning the Next Engineering Era Our speakers include: → Ralf Schmidt – Infineon Technologies → Junjie Tang – AWS ProServe → Daniel Höllisch – AGCO → Dr. Daniel Isemann – Cognizant Mobility If you lead engineering, technology or product strategy, join the discussion: Where should you focus AI investment? How can AI shorten development cycles? What does it take to scale beyond individual use cases? Bring the questions shaping your roadmap. Compare perspectives with speakers and fellow decision-makers on what it takes to move from ambition to execution. 📅 October 8, 2026 | 11:00–17:00 📍 Allianz Arena, Munich Explore the full speaker line-up and register now: https://lnkd.in/e3imx8md Visual created with AI assistance. #AIinEngineering #EngineeringLeadership #AITransformation #SoftwareDefinedVehicle #CognizantMobility

Different trucks. One software platform. How much software can you truly reuse? A shared platform creates the foundation. The engineering determines how much development work you avoid repeating. Across truck brands and vehicle variants, the same function may need to work with different hardware, interfaces and operating requirements. Without clear separation, shared functionality can turn into multiple implementations to maintain. Making reuse work means: ▪️ Separating shared functionality from hardware dependencies. ▪️ Defining stable interfaces and managing variants deliberately. ▪️ Assessing the impact of changes and validating affected vehicle configurations. At Cognizant Mobility, we bring together embedded and application software development, AUTOSAR expertise and system integration to make reuse work in practice. The goal: develop common functionality once, adapt where necessary and keep changes manageable throughout the vehicle lifecycle. What limits software reuse most in your projects: hardware dependencies, interfaces or validation? Visual created with AI assistance. #SoftwareDefinedVehicles #CommercialVehicles #EmbeddedSoftware #AUTOSAR #CognizantMobility

Join us for an AI event at Munich’s Allianz Arena on October 8. The AI-Driven Game: Winning the Next Engineering Era An exclusive event for senior leaders on the future of engineering – and how to turn AI potential into measurable business results. From passenger cars and commercial vehicles to agricultural machinery and beyond, AI is becoming part of every engineering project. Delivering business impact takes more than technology. Together, we’ll explore: → Where will the next wave of AI-driven value come from? → What will it take to radically shorten development cycles? → Which capabilities and platforms will enable AI at scale? Bring your perspective. Join the dialogue. 📅 October 8, 2026 📍 Allianz Arena, Munich Register now: https://lnkd.in/e3imx8md #AIinEngineering #EngineeringLeadership #AITransformation #SoftwareDefinedVehicle #CognizantMobility

Agricultural machines are built to last for decades. Their software cannot stand still. A tractor or harvester may remain in operation for more than 20 years. Its software, however, may require several updates a year as functions and AI models evolve. Many existing E/E architectures were not designed for these different lifecycles. Software functions are often tightly coupled to individual control units, making them difficult to update independently of the hardware. Replacing an ECU whenever functionality changes is neither scalable nor economically viable. That is why we are working with our customers on software-centric architectures for agricultural machinery that better decouple hardware and software lifecycles. Within the technical limits of the platform, software functions can be updated and extended without turning every change into a hardware replacement project. This also creates the architectural foundation for Edge AI. Camera and sensor data can be processed directly on the machine. Crops, obstacles and field conditions can be detected locally, and decisions made in real time — even when operating conditions are demanding and a reliable connection to the cloud cannot be assumed. Hardware will continue to evolve. But it should not have to change every time the software does. Agricultural machines are built to last. Their capabilities must be built to evolve. Want to find out more? Contact us directly or leave a comment. #SoftwareDefinedMachines #AgriculturalMachinery #SoftwareArchitecture #EdgeAI #CognizantMobility