Enterprise Data Management for AI-Enabled Chip Design
Keysight Technologies introduces SOS Enterprise to standardize development data and enable the scalable integration of AI into semiconductor design and verification processes.
www.keysight.com
Keysight Technologies has introduced SOS Enterprise, an extension of its platform for managing development data. The goal is automated traceability and compliance control in distributed semiconductor and electronics organizations. The solution builds on the existing SOS Core architecture and addresses a structural problem faced by many companies: fragmented engineering data spread across isolated tools and file systems.
In semiconductor and electronics development, both design complexity and data volume increase with each new technology generation. Engineering teams generate large amounts of layout files, simulation results, verification artifacts, and IP libraries. When these assets are managed manually or stored in separate repositories, version conflicts, redundant work, and limited traceability arise.
This fragmentation also makes it more difficult to use AI in engineering. Machine-learning models require structured, consistent, and traceable datasets to operate reliably at industrial scale. Without standardized metadata, versioning, and data provenance, AI-driven design and verification tools cannot be stably integrated into production workflows.
How the platform works
SOS Enterprise acts as a unified system of record that converts distributed development data into versioned, traceable, and reusable assets. The platform standardizes data-governance structures across multiple sites and regulatory environments, thereby supporting global development organizations.
Key technical mechanisms include:
- Version-controlled management of design and verification files as structured assets
- Automated traceability between design revisions, validation results, and associated IP
- Central metadata models to ensure consistent data provenance
This structured data foundation creates the prerequisites for AI-driven workflows in chip design. Typical use cases include automated design-rule checks, simulation-based optimization, and pattern recognition in large regression test datasets.
Compliance and security in regulated industries
The platform integrates enterprise-level compliance mechanisms, including audit trails, role-based access control, and software bill-of-materials (SBOM) tracking. These functions are particularly relevant for semiconductor suppliers operating in regulated sectors such as aerospace, defense, or automotive, where documentation requirements and traceability chains are mandatory.
Advanced security features include granular permission models, geofencing policies, and region-specific compliance restrictions. This allows sensitive IP to be protected while still enabling cross-site development processes.
By embedding these controls into existing engineering workflows, the platform reduces administrative overhead without fundamentally changing established design processes.
Reducing manual processes in the digital supply chain
In many organizations, maintaining traceability requires significant manual coordination, for example when reconciling file versions or documenting design dependencies. SOS Enterprise automates these tasks across the entire development lifecycle and systematically links data origin, change history, and validation results.
In the context of a digital supply chain, this structure increases transparency between internal teams and external partners. Validated design building blocks can be identified and reused across locations, making IP utilization more efficient.
According to Keysight, initial customer deployments have led to improved cross-site IP reuse, faster project coordination, and reduced operational effort related to manual data reconciliation.
Prerequisites for scalable AI integration
The adoption of AI in semiconductor design depends heavily on data quality and structure. Separate repositories and inconsistent file management limit the reliability of AI-driven design processes. Through automated traceability and standardized data governance, SOS Enterprise provides the infrastructure required for scalable AI integration.
The platform does not introduce new design algorithms; instead, it addresses the underlying data infrastructure an area that is increasingly regarded as the technical foundation for AI-enabled development environments.
www.keysight.com
