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How tech firms and automakers are breaking down siloes to fuel innovation

"The true definition of partnership is taking shape – an alliance-led approach where the whole industry leans into the idea that we’re on this innovation journey together..."

The true definition of partnership is taking shape – an alliance-led, collaborative approach where the whole industry leans into the idea that we’re on this innovation journey together to solve problems and work through challenges, even when the answer isn’t obvious,” says Wendy Bauer, VP and GM, Automotive and Manufacturing, at AWS.

Sitting down with The Stack, Bauer and MongoDB’s Industry Field CTO, Boris Bialek, say that automakers are realising that in order to thrive they must adapt, innovate, and collaborate more than ever before. 

The rise of the “software-defined vehicle” and industry digitalisation touches everything from driver experience to predictive maintenance, via supply chain optimisation – the levels of industry change happening mean that operating in silos is no longer an option for forward-thinking firms.

The result is a growing appetite to partner with tech giants, start-ups and other innovators to accelerate transformation – whether that is of the in-vehicle experience, or downstream across complex supply chains.

A rise in "very deep collaborative environments"

Bauer is humble about the lessons that AWS has had to learn along the way. Her years of work with automotive partners have been filled with “incredible learnings,” the majority through “very deep collaborative environments,” she says. She gives the example of technology capabilities delivered through a mutually educational deep partnership with BMW.

What’s forming, albeit still with some way to go, is an interconnected network of industry leaders and their technologies that enhance the driving experience and improve overall safety and convenience. One example of this is COVESA, a technology alliance focused on creating open standards and technologies that accelerate innovation for connected vehicle systems – MongoDB, notes Bialek, is a highly engaged member.

Another is the SDV Alliance, a new “collaboration of collaborations” that includes industry groups COVESA, ETAS SOAFEE, and Eclipse SDV (all of which AWS is a member of) – set up to drive a “harmonization of standards and development methodologies” for software-defined vehicles.

It’s not always been an easy ride…

“The automotive industry works with deep supply chains but the notion of partnering has not always been consistent,” says AWS’s Wendy Bauer.

“Despite exponential growth in the size of data and the complexity of vehicle software, for a long time the various functions of a vehicle were still being developed through traditional OEMs who each had their own layer going through verification and validation,” she tells The Stack.

“But the notion of how you collaborate and build trusted relationships is now shifting as auto companies look to innovate faster. Modern day tools allow you to collaborate and develop on a single engineering software development platform to speed time to market and develop more efficiently," Bauer says.

MongoDB’s Industry Field CTO, Boris Bialek, agrees, telling The Stack: “It really is a team effort now. You work through alliances... really partner and it is very collaborative. Then the OEMs differentiate themselves on the customer experience” – rather than the undifferentiated heavy lifting of writing software or deploying technology infrastructure.

See also: How SEGA’s Felix Baker delivered a data transformation

MongoDB launched Atlas for Manufacturing and Automotive; a new initiative that helps organisations innovate with real-time data and build applications on top of it. Think everything from real time visibility on raw material shipment and inventory tracking, to applications that use the high volumes of time series data generated by machines, robots, and factory workers to drive efficiencies.

Highlighting AWS and MongoDB’s close work in this sector, he notes that there is huge scope for application modernisation and converge platforms even at the design stage – where vehicle makers need to manage data from multiple sources and formats including CAD files, simulations, product test results and customer feedback.

“Many legacy systems are incorporated at this stage to handle data movement and aggregation. Unstructured data needs to be contextualised and consumed via various applications. Not having a streamlined data infrastructure results in siloed data, redundant work, and slow collaboration between departments” as MongoDB puts it.

Reinventing the vehicle experience

Examples of successful collaborations to drive innovation in the auto industry are now aplenty. Stellantis, the automaker behind brands like Alfa Romeo, Chrysler, Peugeot, Jeep and Maserati, wants to completely reinvent how vehicles are designed, engineered and operated. It plans to invest more than €30 billion in electrification and software through 2025 and nearly triple the number of its connected cars on the road by 2030.

Using AWS services that automatically scale on demand, Stellantis and Amazon have created a cloud-native “Virtual Engineering Workbench” to expedite development of software-defined vehicles, for example.

Check out: MongoDB’s CPO Sahir Azam on data sovereignty and empowering developers

MongoDB Atlas on AWS meanwhile is the backbone of Volvo Connect – a portal for fleet managers that is expected to hit two billion events daily within two years. (Volvo’s team migrated 8TB of data from a self-managed database instance in just 2.5 days to the MongoDB Atlas managed service, which provides a suite of capabilities transforming how Volvo manages data.)

Accelerating the development lifecycle

BMW also chose AWS as the cloud provider for the next-generation advanced driver assistance system (ADAS) in development for its ‘Neue Klasse’ class of vehicles launching in 2025. ADAS uses advanced software and onboard sensors to provide driver warnings, automated braking and steering functions to make driving safer and more comfortable.

Based on a common reference architecture, ADAS uses AWS services to speed up BMW’s development life cycle, for example providing the framework to process, catalogue and store millions of miles of real-time driving data in Amazon S3. Engineers and data scientists can then search, identify and visualise relevant driving scenes to develop and train models using Amazon SageMaker, AWS’s service for building, training, and deploying machine learning models in the cloud and on the edge.

“In the next decade, consumer habits and expectations will drive more changes in the automotive industry than we’ve seen over the past 30 years,” says Dr. Nicolai Martin, SVP, Driving Experience, at BMW Group.

“This is just the beginning of a new era of highly automated driving, fueled by innovations in technology and engineering” he adds.

Better together

AWS has carefully crafted its own network of innovation partners to meet the needs of customers such as BMW and Stellantis, including MongoDB.

It awarded the AWS Automotive Competency designation to MongoDB for demonstrating deep technical skill and expertise in delivering specialised automotive solutions on AWS – and MongoDB Atlas, the fully-managed and flexible developer data platform, is now an AWS recommended partner for automotive solutions; Volvo was clearly a trailblazer.

Together the two companies are leveraging cutting-edge technologies like generative AI to transform the automotive industry. MongBB for example is working with one European OEM, for instance, to tape and vectorise the sound of its cars in MongoDB. Out of the VIN database and the text search about each model, they can see what issues exist in the vehicles. 

A sound might imply, for instance, that the cylinder head is loose. Recognising this, the system will immediately present how to fix it from all the manuals sitting in LLMs and, through the click of a button, order the required parts – “an automated loop which just ten years ago was unthinkable,” says Boris Bialek, Field CTO, Industries, at MongoDB.

“Companies would lose money, time and resources dealing with issues like this. There are a lot of cool things happening. Historically, each factory had a knowledge book in the hands of individuals who knew exactly which machine misbehaved on certain days. Now thanks to the cloud we can see behaviour on a global scale, across multiple OEMs and thousands of machines and come to corrective measures early on, saving millions.

He adds: “Partnerships with the likes of AWS and MongoDB have sped that journey tenfold. AWS brings a lot of knowledge down to the vehicle level, and we deliver the data view level. This kind of collaborative effort is quite new in the manufacturing industry. Before you only talked to one manufacturer. Now, everybody's in the room talking about software-defined vehicles. The consumer experience is now embedded from the mobile device, to the cloud, to the car, and all in return. OEMs can't build all this stuff themselves anymore. It's exciting for all involved.”

Delivered in partnership with MongoDB

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