Siemens Fleshes out More of their AI in Verification Story

While Cadence and Synopsys were sharing a lot of detail over the past few years about what they were doing in AI, Siemens EDA seemed content to offer a very general picture about their intentions without getting into a lot of detail. At DVCon 2025 they finally pulled back the curtain. Why wait until now to announce?

Darron May (Director of AI Product Management at Siemens Digital Industries) hosted the session and pointed to the depth Siemens can already boast in AI – 1400 AI experts, nearly 4000 patents – developed over many years working with large enterprises. Also note Darron’s title – he stressed that Siemens is now one tech company, not Siemens plus Siemens EDA. The Siemens centralized AI team have been building a platform for the EDA guys, who have been integrating with and building on this broader expertise to develop and roll out their broader AI gameplan. Makes sense to me. Takes a little longer to get to announcement but ensures they can start from a proven base.

A quick recap on why AI in EDA

Darron opened with the obligatory marketing nod to chips becoming more complex (in part thanks to AI content), together with projections that the industry is going to be short 27,000 expert designers by the end of the decade.  All true but I’d like to add my own thoughts. The highly visible part of this growth, around AI accelerators from Nvidia, AMD, and the hyperscalers, is the tip of the iceberg. The real volume is in AI applications: wearables, smart homes, transportation, smart offices, medical, industrial, utilities, etc. IoT applications alone are expected to top 6 billion units by 2030. Those are going to be built on embedded designs customized with sensing, AI, and communications components to differentiate and be super cost and power effective.

These “applications” companies/business units have design and AI expertise, but they can’t build giant teams of experts because there aren’t enough experts. They must rely even more heavily on EDA, IP, even packaging technologies to meet their goals. You start to see why the industry needs to spin up more designers, including AI-assisted designers, to keep pace with demand.

Siemens advances in AI for verification

Siemens are broadly leveraging three types of AI in this domain: analytical based on unsupervised learning (ML), predictive based on ML and statistical analysis to predict future behaviors, and generative/agentic support based on LLMs. This is quite in-line with similar effort from big EDA companies.

The announcements aren’t groundbreaking in this industry but bear in mind that Siemens are catching up. I’ll start with their ViQ (Questa verification IQ) platform. The Coverage Analyzer already offers (in production) analysis to predict patterns and holes in coverage, provide root cause analysis and suggest solutions. For Debug, they have early adopter engagements in bad commit prediction, root cause prediction and signature prediction. And in regression navigation they have early adopters in smoke test prediction.

QCX (coverage acceleration), PSS Assist (GenAI for PSS) and Doc Assist (auto-generating docs) are all in early adopter engagements.

For creation, they are promoting Property Assist (GenAI assertion generation with extensive checking through static and formal tools to validate correctness) – this is the early adopter stage, whereas CDC Assist and RDC Assist (massively distilling crossing violations) are already in production.

There are multiple other capabilities planned but in the interests of avoiding future-looking statements I will leave those out 😀.

In summary, several capabilities in production and more on the way through early deployment. One thing that stuck with me – Siemens has that central AI team as a potential differentiator over others in the design and verification world. Worth watching. You can explore Siemens capabilities in EDA HERE.