HomeTechnologyArtificial IntelligenceKeysight's Software Solution for Reliable AI Deployment in Safety-Critical Environments

    Keysight’s Software Solution for Reliable AI Deployment in Safety-Critical Environments

    Keysight Technologies, Inc. introduced Keysight AI Software Integrity Builder, a new software solution designed to transform how AI-enabled systems are validated and maintained to ensure trustworthiness. As regulatory scrutiny increases and AI development becomes increasingly complex, the solution delivers transparent, adaptable, and data-driven AI assurance for safety-critical environments such as automotive.

    AI systems operate as complex, dynamic entities, yet their internal decision processes often remain opaque. This lack of transparency creates significant challenges for industries, such as automotive, that must demonstrate safety, reliability, and regulatory compliance. Developers struggle to diagnose dataset or model limitations, while emerging standards — such as ISO/PAS 8800 for automotive and the EU AI Act- mandate explainability and validation without prescribing clear methods. Fragmented toolchains further complicate engineering workflows and heighten the risk of conformance gaps.

    Keysight AI Software Integrity Builder introduces a unified, lifecycle-based framework that answers the critical question: “What is happening inside the AI system, and how do I ensure it behaves safely in deployment?” The solution equips engineering teams with the evidence needed for regulatory conformance and enables continuous improvement of AI models. Unlike fragmented toolchains that address isolated aspects of AI testing, Keysight’s integrated approach spans dataset analysis, model validation, real-world inference testing, and continuous monitoring.

    Core capabilities of Keysight AI Software Integrity Builder include:

    • Dataset Analysis: Analyse data quality using statistical methods to uncover biases, gaps, and inconsistencies that may affect model performance.
    • Model-Based Validation: Explains model decisions and uncovers hidden correlations, enabling developers to understand the patterns and limitations of an AI system.
    • Inference-Based Testing: Evaluates how models behave under real-world conditions, detects deviations from training behaviour, and recommends improvements for future iterations.

    While open-source tools and vendor solutions typically address only isolated aspects of AI testing, Keysight closes the gap between training and deployment. The solution not only validates what a model has learned, but also how it performs in operational scenarios — an essential requirement for high-risk applications such as autonomous driving.

    Thomas Goetzl, Vice President and General Manager of Keysight’s Automotive & Energy Solutions, said: “AI assurance and functional safety of AI in vehicles are becoming critical challenges. Standards and regulatory frameworks define the objectives, but not the path to achieving a reliable and trustworthy AI deployment. By combining our deep expertise in test and measurement with advanced AI validation capabilities, Keysight provides customers with the tools to build trustworthy AI systems backed by safety evidence and aligned with regulatory requirements.”

    With AI Software Integrity Builder, Keysight empowers engineering teams to move from fragmented testing to a unified AI assurance strategy, enabling them to deploy AI systems that are not only performant but also transparent, auditable, and compliant by design.

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