In Brief Modern digital cockpits are complex systems-of-systems (SoS), necessitating meticulous software integration and comprehensive validation to ensure reliable, safe, and user-friendly in-vehicle experiences. Integration goes beyond simply combining software...
In Brief: Agile testing is transforming automotive software development with faster, adaptive validation processes. Continuous Integration and Continuous Testing (CI/CT) reduce bugs and improve quality through real-time testing. Simulation-based validation and digital...
In Brief Connected car technology is revolutionising the e-mobility experience, turning EVs into intelligent, communicative companions. Real-time diagnostics, proactive maintenance, remote control, and personalised interactions elevate the driving experience. Acsia...
In Brief Telematics represents the integration of telecommunications and informatics within vehicles, revolutionising the automotive landscape. Acsia is a leading player in telematics innovation, shaping smarter, safer, and more efficient vehicles for consumers and...
Artificial intelligence (AI) and machine learning (ML) are revolutionizing software development, particularly in the evolving automobile industry, where software-defined vehicles (SDVs) rely heavily on code for features and performance. These technologies promise to enhance productivity, streamline workflows, and reduce costs—benefits that are crucial for the cost-sensitive automotive sector.
However, challenges remain, including integration difficulties and concerns regarding privacy, functional safety, and compliance. By leveraging AI and ML, software engineers can automate tasks like code generation and debugging, allowing them to focus on more complex, creative aspects. Success requires expertise in the automotive-specific development environment and ensuring compatibility with existing standards and processes.
LiLA, an AI-powered Developer Suite forms the bedrock of Acsia’s AI capabilities in automotive SW development.
*In pipeline
Acsia is committed to working closely with OEMs and their Tier-1 suppliers to fully harness the power of AI Copilot LiLA and enable significant gains in efficiency, productivity, and cost savings across production programs.
LiLA helps development teams save considerable effort & time spent on the analysis of DLT logs and reporting anomalies, detection of duplicate bug tickets, unit testing, and code optimization.
LiLA simplifies and saves time on requirements engineering, generating software architecture and design, developing code with engineered prompts, complying with MISRA C/C++ guidelines, unit testing, and code refactoring, dead code elimination, and performance optimization.
LiLA simplifies the management of large code volumes in maintenance projects through refactoring and optimization. It minimizes errors, enhancing software reliability and consistency.
LiLA automates compliance checks against standards, ensuring the software meets all requirements without rejections or rebuilds, allowing for first-time accuracy.
In Brief: Agile testing is transforming automotive...
In Brief Artificial Intelligence (AI) is reshaping...
