LiLA Agentic AI Platform

Significantly enhance software development efficiency and productivity.

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.

How Acsia Can Help?

LiLA Agentic AI Platform forms the bedrock of Acsia’s AI and ML capabilities in automotive SW development.
  • Requirements Engineering*
    • SYS and SWE
  • Standards Compliance
    • MISRA C/C++
    • ASPICE*
    • ISO 26262*
  • Defect Management
    • Log Analyzer
    • Defect Analyser and Duplicate Detection
  • Feature Modelling*
  • RAG (Retrieval Augmented Generation)
  • Diagram interpreted generation using vision models
  • AUTOSAR Chatbot
  • Norms Analyzer
  • Code Development
    • Generate design (SWE.2) from SWE.1 as input​
    • Develop code using prompts generated from SWE.2
    • Create Unit Tests using AI (SWE.4)​
    • Generate code coverage​
  • Code Optimization
    • Code Refactoring
    • Dead Code Elimination
    • Loop Optimization
    • Function Inlining
    • Reduce Code Complexity
*In pipeline

Acsia is committed to working closely with OEMs and their Tier-1 suppliers to fully harness the power of LiLA Agentic AI Platform and enable significant gains in efficiency, productivity, and cost savings across production programs.

Project Highlights

1. Validation of automotive component suppliers is time consuming. Too many suppliers. Complexity of data analysis – AI can streamline and analytics to generate recommendation report based on criteria provided. Relevant to OEM and T1.

2. Log analysis and anomaly detection, duplicate defects detection – both are time consuming. Ten thousands of tickets. Logs will be GB size files. Relevant to OEM and T1.

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If automotive HMI in English has to be translated to another language like Arabic or Mandarin or Spanish: manual translation of thousands of words and strings is time consuming and expensive.

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Hear From Experts
Vasantharaj G Pillai
VP Technology & Innovation
With Acsia since 2014
“AI and ML are revolutionizing automotive software development by streamlining processes, automating tasks like defect management and code generation, and ensuring compliance with industry standards. Acsia’s LiLA Agentic AI Platform accelerates this transformation, enhancing productivity, reducing development time, and ensuring high-quality, compliant software — helping OEMs stay ahead of competition.”
OEM Production Program Experience:
Tier-I Experience:
Why Acsia?
A Decade of Excellence
10 years of experience in automotive software development for the world’s leading automakers.
LiLA Agentic AI Platform
Acsia’s LiLA Agentic AI Platform is exclusively tuned for automotive SW development use cases.
Experience across IVI, e-Mobility, and Telematics
Acsia engineers have deep domain insights gathered from delivering numerous projects in in-vehicle infotainment, e-mobility and telematics to train the AI models.
AUTOSAR, Android Automotive, Automotive Linux, Verification & Validation, HMI capabilities
Acsia engineers have proven expertise in automotive industry-relevant capabilities to train the AI models.
Isolated, Offline/Local and Secure
LiLA is deployed locally and operated offline ensuring information security by preventing the sharing of vital data online.
2-months Consulting
Framework and criteria to jointly identify use cases that can offer the greatest value.
2 Deployment Models
Custom UI (chat mode) and Microsoft Visual Studio Code IDE integration.
10 years of experience in automotive software development for the world’s leading automakers.
Acsia’s AI-powered developer suite LiLA is exclusively tuned for automotive SW development use cases.
Acsia engineers have deep domain insights gathered from delivering numerous projects in in-vehicle infotainment, e-mobility and telematics to train the AI models.
Acsia engineers have proven expertise in automotive industry-relevant capabilities to train the AI models.
LiLA is deployed locally and operated offline ensuring information security by preventing the sharing of vital data online.
Framework and criteria to jointly identify use cases that can offer the greatest value.
Custom UI (chat mode) and Microsoft Visual Studio Code IDE integration.
What’s In It For You

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.

Frequently Asked Questions

Acsia’s LiLA Agentic AI Platform is an AI-powered developer suite tailored for the automotive industry. It automates tasks such as defect management, document analysis and code generation, thereby increasing productivity, streamlining workflows, and reducing costs in the automotive software development life cycle (SDLC).

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Retrieval Augmented Generation (RAG) in Acsia’s LiLA Agentic AI Platform streamlines the process of managing automotive requirements by quickly retrieving relevant information from extensive standards and documentation. This eliminates the need for manual searches, significantly reducing turnaround time (TAT) and ensuring accuracy in requirement interpretation.

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LiLA can automate various tasks, including:​

  • Defect management
  • Document analysis
  • Code generation
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The suite is deployed locally and operates entirely offline, ensuring that sensitive automotive data remains secure and never gets shared online. This approach prevents unauthorized access and safeguards vital information from potential breaches.

Additionally, LiLA automates compliance checks against industry standards, ensuring that the software meets all regulatory and safety requirements on the first attempt. This eliminates the need for rework or rejections, enhancing both security and development efficiency.

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Yes, LiLA has been successfully deployed by a leading German OEM. Many POCs are underway.

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