Empowering the
Automotive Industry to
Build Software-Defined
Vehicles

Predictive maintenance

The cost of repair when the fault grounds the vehicle is 10x higher than fixing it when the first symptom occurs. That’s why most mobility providers and OEMs build predictive maintenance systems based on machine learning algorithms – to reduce the maintenance cost of vehicle fleets. With sophisticated algorithms based on real-time car telemetry and status information, as well as historical data, some of the costly repairs can be predicted and avoided.

Efficient remote operations leveraging Vehicle Shadow and seamless connectivity

While the end goal for the connected car is seamless connectivity, built upon multiple mediums of communication complementing each other depending on the situation, there are still areas with no network coverage. To mitigate this kind of connectivity problem, vehicle manufacturers are implementing the Digital Twin concept. The vehicle representation in the cloud holds all required statuses and proxies the remote operations. This means that for the end-user the vehicle remote operations are always available and also greatly simplifies the communication. Problematic scenarios are offloaded to the Vehicle Shadow system sitting on top of the IoT platform.
Grape Up helped Porsche build their Digital Twin system for the Connected Car platform.

Improve latency for V2X communication with 5G mobile network

Modern autonomous driving systems highly benefit from internet connectivity. Data coming from in-vehicle sensors is accompanied with the data from the vehicle environment – urban infrastructure, traffic lights, surrounding vehicles, pedestrians’ mobile devices, or internet APIs all help in better prediction of driving conditions.
The ADAS systems require very-low latency to operate – as the reaction time in case of emergency has to be measured in milliseconds. This kind of latency, with improved bandwidth, became a reality with the popularization of 5G technology and networks.

Grape Up helps one of its OEM customers to build a system for managing the connectivity between the vehicle and cloud – starting from the connectivity activation, through lifetime and runtime operations, to data plans management. The system is integrated with all world-renowned MNOs, including Cubic Telecom, T-Mobile, Vodafone, or China Unicom.

Integrate 3rd party apps/services into vehicles to open new revenue streams

Today's infotainment systems are a bit like smartphones. Navigation, entertainment features, internet browsing, calling, and even detailed car settings are all mostly done through this digital touchpoint.
Allowing 3rd parties to be able to integrate the completely new application and showcase them on the infotainment screen opens completely new revenue streams for the OEMs. Applications like Spotify are heavily used by drivers, but also corporate users may have their fleet management systems integrated. Skoda Auto recently showcased a use case, where commercials of the nearby special offers appear on the navigation system turning their infotainment system into advertising media.

Improving user experience by modernizing Connected Store

Connected Stores enable manufacturers to offer a wide range of options and features without physically modifying their vehicles. This provides greater flexibility to meet their customers' evolving needs and preferences while also reducing the cost and time associated with physical upgrades.
Implementing integrated payments can further streamline purchasing physical products and on-demand services. Creating a contemporary e-commerce platform with a functional and user-friendly front-end is crucial to ensure the customer's smooth and uninterrupted experience.

As a software development company specializing in the automotive industry, we offer a unique solution to enhance the user experience of vehicle owners by creating Connected Stores.

Integrating subscription-based offerings, payments, and interactive interfaces in the vehicle

Subscription-based everything within the automotive industry refers to the concept of offering software-based services and vehicle features on a subscription basis. This means that customers pay a recurring fee instead of purchasing a feature outright to access and use these features. For example, manufacturers can use a subscription-based model to offer connected car services, advanced safety features, and autonomous driving capabilities.

From a software point of view, this subscription-based model enables vehicle manufacturers to offer their customers a wider range of features and options while also providing a steady revenue stream. It also allows for more frequent and efficient software updates, enhancing the functionality and performance of existing features.

This can provide customers with a more cost-effective and flexible option rather than paying for services or features up-front. Moreover, the integration of payments across different channels ensures a consistent experience.

Configuring software features for different markets

By offering employees the ability to configure and manage software features based on market needs, manufacturers can provide a more customized and differentiated user experience for customers in different markets. Offer Management Configurators used for this purpose provide a user-friendly interface for configuring and managing a wide range of vehicle features and options.
Offer management configurators enable efficient management and configuration of vehicle software features, reducing errors and improving customer satisfaction. Manufacturers can tailor their product offerings to specific markets, increasing sales and customer satisfaction.

Analyzing behavioral data and driving patterns based on car telemetry

Analyzing behavioral data allows automotive companies to unlock the potential for cost reduction, open new revenue streams, or even create new business models.
In the insurance industry, it is a fundamental feature allowing for pay-per-use offering as well as granting safe drivers with discounts for the insurance policies.
For the automotive industry, however, it can be treated as the base for predictive maintenance – it allows to plan maintenance works based on the usage of car components, but also to help to analyze the range of the electric car battery based on the long term driving patterns.
For the rental car business, it allows to offer discounts for safe drivers but also allows to propose features and vehicles most suitable for them based on the patterns of their previous behavior.

Integrating OEMs telemetry APIs for shared mobility purposes

Integrating OEM’s Telemetry is one of the crucial aspects allowing to unlock new revenue streams as well as reducing operational costs for the mobility providers. One of the key unlocked features is to allow for the bi-directional communication between the car and the user. Locating the car in the parking lot, opening/closing the car from the mobile application, or checking the fuel level significantly increases user satisfaction. On the other hand, analyzing the behavioral data of the driver or the car telemetry itself allows insurance providers to create pay-per-use insurance or discounts for safe drivers.
Grape Up has a proven track record of designing and developing complete telemetry platforms, creating APIs for OEMs that can later be exposed for 3rd parties but also consuming APIs of different OEMs and integrating these data with internal systems.

Geofencing for theft prevention and location-based services

Geofencing increases the safety of fleet companies' operations by adding the ability to track the location and alert on breaking the agreed boundaries. This is most often a case when a vehicle gets stolen, or a customer tries to avoid higher charges for going abroad. With location-based services, the rental or fleet company is immediately notified of such violation and can act appropriately.
One of Grape Up’s customers – a rental car company, developed a Stolen Vehicle Identification system based on OEM’s Telemetry and Geofencing. During just 6 months from launching this feature and integrating it with its internal fleet management system, the company was able to locate 356 missing (stolen or impounded) cars, thus saving hundreds of thousands of dollars by recovering cars, as well as administration costs.

Reduce manual labor and improve customer experience with touchless mobile apps

Breakthrough of the COVID-19 pandemic completely changed the way we work and live thus also changing the way we travel, rent, buy or lease cars. It is now crucial for mobility providers to allow their customers for a counter-less rental experience allowing them to avoid queues, but also unnecessary contact.
For one of its customers, Grape Up has designed and developed a touchless system allowing clients to rent a car directly from a mobile phone. Complete customer journey comes to selecting a car, buying insurance and additional features, paying through mobile phone then locating and opening/closing the car - all from the mobile device. The platform is integrated with OEMs Connected Car platform APIs and an internal telematics system, making the system robust and responsive.

Recommendation engines based on AI/ML to boost sales

In the modern automotive business, not only traditional dealerships or over-the-counter sales drive revenue for today's mobility providers, vehicle manufacturers, and OEMs. Today, recommendation engines and mobile applications generate an increasing amount of sales records. Acknowledging the business value of recommendation systems, Netflix estimated that their recommendation engine is worth $1bln yearly.
Rental car companies use these solutions in upselling to encourage customers for additional insurance, a higher grade vehicle, and other additional features. Leveraging recommendation systems vehicles enterprises increase sales and improve customer experience.
Our data science and data engineering departments have a proven track record of creating machine learning algorithms and combining them with e-commerce systems allowing automotive companies to take benefit from recommendation engines based on previous purchases.

Understand your ML predictions and reasoning – Explainable AI

Artificial Intelligence has proven to be a good way to tackle problems, which seemed impossible before. For the general audience, most of the ML is a black box, which accepts data and responds with prediction or identification. Algorithms are complex and hard to understand for non-data scientists. With explainable AI, the problem resolution path can be exposed to customers and stakeholders, making the bottlenecks and reasons for wrong reasoning visible.
Grape Up Data Scientists can help you build an ML system allowing stakeholders, developers, and customers to comprehend the prediction process and, as a result, have more trust in the results.

Minimize support costs and prevent data loss with a scalable, common data streaming platform

Building multiple platforms for storing the data is costly, hard to maintain, and can result in data loss due to incorrect handling. This problem can be resolved by building a common data streaming platform able to handle real-time data for the whole enterprise. Built with scalability and redundancy in mind this kind of platform can effectively withstand and resist problems in having a system of distributed, different platforms and storage systems. The support cost is also lower.Grape Up experts are highly experienced in creating and maintaining efficient and scalable data streaming platforms based on Kafka that are currently being used among Grape Up customers representing automotive and financial institutions around the world.

Democratize access to the data for the whole enterprise through ETL and data mesh

Data is a lifeblood of an organization. Each department generates and gathers enormous amounts of data about customers, products, or the environment. This data can be used to enable new revenue streams by creating better offers and improving understanding of customer needs. Data analytics can also result in reducing the cost by improving the bottlenecks and identifying pain points.Building systems or ML algorithms leveraging the available data can be extremely complicated if the data is siloed and available only inside the department. Democratic access to the data across the enterprise helps to build better products faster and easier while having a single point for data storage makes the operations easier. Storing the heterogeneous data in data lakes and data meshes is easier for developers and data scientists.For one of our customers, Grape Up engineers have already implemented the modern data storage, starting from the ETL/EL(T) system, through the data lake and ML system built on top of it while maintaining enterprise-grade privacy and GDPR compliance.