Ensuring data moves smoothly across multiple disciplines, tools, and globally distributed teams.

In today’s fast-paced electronics design automation (EDA) environment, effective data management has become essential. Growing design complexity, distributed teams, and the accelerating adoption of AI/ML are pushing organizations to rethink how they manage, track, and leverage decades of engineering data.

From manual workarounds to data management

Many engineers discover the importance of data management through hands-on challenges in their own workflows. For example, front-end and analog designers often build custom scripts, tools, and automation to handle simulation data, manage revisions, or coordinate across teams. These challenges highlight a core realization: engineering excellence depends on data excellence.

Industry challenges in data management

1. Complexity Across Projects, Domains, and Tools: Modern semiconductor and system design projects bring together multiple disciplines, workflows, and EDA tools. Data must move smoothly across all of them, often across globally distributed teams. Ensuring consistency, traceability, and accessibility becomes increasingly difficult as project complexity grows.
2. Rising Pressure to Be AI/ML-Ready: The industry is rapidly shifting toward AI-driven workflows. But before meaningful AI adoption can occur, organizations must ensure their data is clean, labeled, organized, and cataloged. Without this foundation, AI initiatives struggle or fail outright.

Solving these challenges

Keysight SOS is designed to bring structure, intelligence, and scalability to engineering data management. It serves as a centralized system that connects teams, tools, and workflows across the entire design lifecycle.

Key capabilities:

• Seamless Integration Into Existing EDA Workflows: SOS integrates directly with the tools engineers already use, eliminating disruption and ensuring data flows automatically into a unified repository.
• Creation of Organizational Knowledge: By centralizing data, SOS turns scattered artifacts into an accessible, searchable knowledge base that supports engineering teams, management, and future AI/ML systems.
• Performance at Enterprise Scale: Traditional systems like Git and SVN struggle with large analog, RF, and mixed-signal datasets. SOS handles gigabyte-scale files efficiently, enabling fast check-in, check-out, and versioning operations across global teams.

Together, these capabilities bridge the gap between today’s workflows and tomorrow’s AI-driven engineering environments.

Real customer example: A large global design house

A major analog and mixed-signal design organization—150–200 engineers, multiple worldwide sites, and 50–60 active projects per year—faced:

• Fragmented data stored across legacy systems
• Difficulty reconstructing or reusing older projects
• Heavy communication overhead
• Limited visibility into IP reuse

After deploying Keysight SOS, they achieved:

• 50% increase in project throughput
• Bill of materials creation 5–7× faster
• 80% reduction in project-related emails
• Clear reporting on IP consumers across projects and teams

The result was a modernized, unified, and scalable system that improved productivity and increased return on engineering investment.

Ready to transform your data management?

Keysight SOS goes beyond simple version control. It provides the data foundation required for:

• AI/ML pipeline readiness
• Secure, governed, enterprise-wide collaboration
• Centralized visibility into all engineering assets
• Long-term reuse, traceability, and organizational continuity

Data management is no longer optional; it’s the backbone of advanced design workflows. As AI becomes embedded across EDA environments, SOS offers the infrastructure needed to accelerate innovation safely and effectively.

With Keysight SOS, organizations can streamline workflows, centralize data, and prepare for the AI era—all without disrupting engineers’ daily routines.

Maria Castillo

(all posts) María Castillo is a product manager at Keysight Technologies.