AWS for Industries

Category: Automotive

Rivian accelerates production with second-generation AWS Outposts: Improving resiliency and reducing costs

Rivian accelerates production with second-generation AWS Outposts: Improving resiliency and reducing costs

In this blog post, we show how Rivian, a leading innovator in the electric vehicle market, is using this feature to support modern containerized workloads and highly available database architectures for their critical manufacturing workloads at the edge.

How Toyota securely deployed HiveMQ with mTLS on AWS to power Smart Manufacturing

How Toyota securely deployed HiveMQ with mTLS on AWS to power Smart Manufacturing

This blog post covers how Toyota deployed HiveMQ on Amazon ECS with mutual TLS (mTLS) for a secure, scalable IIoT architecture, now scaling beyond a successful single-plant pilot across all North American facilities.

Accelerating Android Builds on AWS: From 3 Hours to Under 5 Minutes with SourceFS

Accelerating Android Builds on AWS: From 3 Hours to Under 5 Minutes with SourceFS

In this post, we explore how SourceFS from Source.dev, running on AWS, transforms the AOSP build experience – reducing end-to-end checkout-and-build time from 3 hours to under 5 minutes. We highlight how leading automotive OEMs are achieving material gains in build velocity, cost efficiency and developer productivity by using SourceFS.

Building a Serverless Supply Chain Management Solution for Automotive Customers with AWS AppSync and Amazon Aurora Serverless

Building a Serverless Supply Chain Management Solution for Automotive Customers with AWS AppSync and Amazon Aurora Serverless

In this blog post, we demonstrate how to build a serverless supply chain management solution tailored for automotive customers using AWS AppSync (a managed GraphQL service) and Amazon Aurora Serverless (an on-demand, auto-scaling relational database). This solution addresses common challenges in managing parts inventory, orders, and shipments by using a fully serverless, GraphQL-based approach.

Driving Intelligent Quality in the Software-Defined Vehicle Era

Driving Intelligent Quality in the Software-Defined Vehicle Era

This blog will cover how PQD enables the transformation of after-sales vehicle quality from a reactive to a proactive, data-driven approach enabled by connected vehicle data, software-defined architectures, and AI/ML services from AWS.

Building an End-to-End Physical AI Data Pipeline for Autonomous Vehicle 3.0 on AWS with NVIDIA

Building an End-to-End Physical AI Data Pipeline for Autonomous Vehicle 3.0 on AWS with NVIDIA

Autonomous Vehicles (AV) development has been maturing and is advancing through clear architectural changes: AV 1.0: classical modular stacks (perception → prediction → planning → control) with hand-engineered interfaces AV 2.0: multi-modal LLM end-to-end (E2E) learned stacks that reduce modularity and improve scaling with data AV 3.0: end-to-end reasoning VLA (Vision–Language–Action) systems that perceive, reason, […]

Multi-Agent AI Solution for Vehicle Fleet Data Discovery and Edge Case Classification

Multi-Agent AI Solution for Vehicle Fleet Data Discovery and Edge Case Classification

Every day, autonomous vehicle (AV) fleets generate terabytes of sensor data—but the rarest, most safety-critical moments often go undetected. Autonomous vehicle manufacturers and Tier 1 suppliers face a specific challenge: identifying which driving scenarios their vehicles encounter and deciding which edge cases require safety validation. As fleets grow, organizations cannot scale manual review to find these rare […]

DR Strategies for Connected Mobility Workloads, Part 1: Backup and Restore

DR Strategies for Connected Mobility Workloads, Part 1: Backup and Restore

Introduction Connected Mobility (CM) integrates vehicles, infrastructure, and data analytics to enhance user experience, safety, and reduce emissions. System resilience is critical as disruptions can cause: 1/direct customer impact on vehicle remote functions 2/brand reputation damage through negative publicity 3/manufacturing disruptions 4/revenue loss and legal consequences. Disaster Recovery (DR) is essential to prepare for natural […]

Accelerating mainframe modernization

Accelerating mainframe modernization: How Toyota Motor Europe (TME) uses Amazon Bedrock to automate legacy code documentation

Toyota Motor Europe NV/SA (TME) oversees the wholesale sales and marketing of Toyota, GR (GAZOO Racing), Lexus vehicles, parts and accessories, as well as Toyota’s European manufacturing and engineering operations. As part of their strategic Legacy Modernization program, TME is exploring the use of generative artificial intelligence (generative AI) to accelerate their mainframe migration efforts. […]