Enterprise Data Management for AI-Assisted Chip Design

[Ahmet Ö.]

## Enterprise Data Management in AI-Powered Chip Design

Keysight Technologies has introduced the SOS Enterprise platform, designed to enable scalable integration of AI into semiconductor and electronic design processes. This platform aims to standardize distributed development data, ensuring automated traceability and compliance control.

In the field of semiconductor and electronic development, design complexity and data volume increase with each technology generation. Engineering teams generate vast amounts of design files, simulation results, verification materials, and IP libraries. When data is managed manually or stored in disparate repositories, issues such as version conflicts, duplicated work, and limited traceability arise.

This data fragmentation complicates the use of AI in engineering. Reliable operation of AI-based models requires organized, consistent, and traceable datasets. SOS Enterprise addresses this need by providing standard metadata, versioning, and data provenance models, enabling the healthy integration of AI-powered design and verification tools into production.

### How SOS Enterprise Works

The platform functions as a unified system of record that transforms distributed development data into versionable, traceable, and reusable structured data. It supports global development organizations by standardizing data management across multiple locations and regulatory environments.

• Management of design and verification files as version-controlled structural assets
• Automated traceability between design revisions, verification results, and related IP
• Centralized metadata models for consistent data provenance

This structure forms the foundation for AI-powered workflows such as automated design rule checks, simulation-based optimization, and pattern recognition in large regression test data sets.

### Compliance and Security Features

The platform includes enterprise-grade compliance mechanisms such as audit trails, role-based access control, and Software Bill of Materials (SBOM) tracking. These features are critical for semiconductor suppliers operating in regulated industries like aerospace, defense, and automotive.

Advanced security measures include granular permission models, geographical restrictions, and region-specific compliance constraints. This protects sensitive IP while supporting cross-location development processes.

### Reducing Manual Processes in the Digital Supply Chain

SOS Enterprise automates processes that typically require manual coordination, such as reconciling file versions or documenting design dependencies. Data source, change history, and verification results are systematically linked throughout the development lifecycle.

This structure increases transparency between internal teams and external partners, enabling efficient reuse of design components across locations. According to Keysight, initial customer deployments have shown an increase in cross-location IP utilization, accelerated project coordination, and reduced effort in manual data reconciliation.

### Requirements for Scalable AI Integration

The use of AI in semiconductor design depends on data quality and structure. Disparate data repositories and inconsistent file management limit the reliability of AI-powered design processes. SOS Enterprise provides the infrastructure that supports scalable AI integration through automated traceability and standardized data management.

While the platform does not introduce new design algorithms, it solves the underlying data infrastructure problems that form the foundation of AI-powered development environments.

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This development raises data management standards in AI-integrated semiconductor design processes, paving the way for more efficient and traceable workflows on a global scale.