DAC News – A New Era of Electronic Design Begins with Siemens EDA AI

AI is the centerpiece of DAC this year. How to design chips to bring AI algorithms to life, how to prevent AI from hacking those chips, and of course how to use AI to design AI chips. In this latter category, there were many presentations, product announcements and demonstrations. I was impressed by many of them. But an important observation is the focused nature of most of this work.  Methods to use AI to accelerate the design flow, or converge on timing faster, and so on. Siemens took a different approach to addressing the requirements of impossible to design chips, however. In its own words, Siemens introduced a comprehensive generative and agentic AI system for semiconductor and PCB design. This approach has significant implications. Let’s take a look at how a new era of electronic design begins with Siemens EDA AI.

The Big Picture

Stepping back a bit, I was struck with a bit of Déjà vu when examining the Siemens announcement and diving into some of the details. Those who have been around EDA for a while will remember The Framework Concept. The idea was to develop an EDA framework that allowed all tools to work off a common data structure and use model. Sharing the user interface meant the best concepts would find their way to all tools. Sharing data models meant all tools could work off the same design description and collectively improve the design in synergistic ways.

It sounded great on paper, but sadly the technology wasn’t mature enough so many years ago. Most, if not all the CAD Framework ideas failed. I recall folks saying, “don’t use the F-word (Framework), or I’ll walk out of your presentation.” Today, we take all this for granted. Every mainstream design flow shares both data and the user experience effectively. The Framework promise was finally delivered.

Fast-forward to DAC 2025 and Siemens is taking this concept to the next level. What if a broad spectrum of AI technologies could be delivered to all development groups in the company? And what if each group could benefit from the substantial infrastructure delivered this way to then add tool-specific capabilities on top of it to create a truly consistent and AI-enabled design infrastructure? This is what Siemens announced at DAC. Let’s take a closer look.

Introducing the Siemens EDA AI System

The starting point for all this is a focus on something Siemens calls industrial-grade AI. The approach defines what’s important to harness AI for chip and PCB design – industrial grade problems. This is in contrast to consumer AI, the ubiquitous version we all see every day. The figure below illustrates the differences.

In my opinion, this important analysis sets up the project for success. Most AI algorithms have a well-defined use model and scope of application. But the way the technology is deployed makes a huge difference. With regard to AI algorithms, the following chart will help to set the scope of application of the Siemens EDA System. In the company’s words, “a powerful hybrid AI system emerges when these AI capabilities are integrated together.”

The Siemens EDA System is being deployed across the company to many development groups. Based on what I saw at DAC, many teams have embraced the technology and there are already many new capabilities as a result. The general deployment model is to leverage generative and agentic AI for front-end tasks and machine and reinforcement learning for back-end tasks. The strategy and the benefits are summarized in the figure below.

There are some guiding principles for this work. They are summarized as follows. I particularly like the last one. The customer base is doing a lot of work to harvest its own unique AI models and strategies. It’s critically important to recognize this and enable it. Siemens seems to have it right.

• Enables generative and agentic AI capabilities across Siemens EDA tools
• Strong data flywheel effect enabled by a centralized multimodal data lake
• Secure with full custom access controls & on-premise / cloud deployment options
• Open and customizable with multiple large language model (LLM) support, ability to add customer data and build custom workflows

First Results Across Key Tools

There was ample proof on display at DAC of the impact of this new approach across the product line. Here is a quick summary of some examples. There will be many more for you to explore.

Aprisa™ AI software: Aprisa AI is a fully integrated technology in the Aprisa digital implementation solution. It enables next-generation AI features and methodologies across RTL-to-GDS capabilities including AI design exploration that adaptively optimizes for power / performance / area. Integrated generative AI-assist is also included, delivering ready-to-run examples and solutions. Aprisa AI delivers 10x productivity, 3x improved compute-time efficiency, and 10 percent better PPA for digital designs across all process technologies.

Calibre® Vision AI software: Calibre Vision AI offers a revolutionary advance in chip integration signoff by helping design teams identify and fix critical design violations in half the time of existing methods by instantly loading and organizing them into intelligent clusters. Designers can then prioritize their activity based on this clustering and achieve a higher level of productivity. Calibre Vision AI also improves efficiency in the workflow with the addition of “bookmarks” that allow designers to capture current analysis state, including notes and assignments, and then foster enhanced collaboration between chip integrators and block owners during physical verification.

Solido™ generative and agentic AI: Solido now harnesses Siemens’ EDA AI system to deliver advanced generative and agentic AI capabilities throughout the Solido Custom IC platform to transform next generation design and verification. Tailored to each phase of the custom IC development process, including schematic capture, simulation, variation-aware design and verification, library characterization, layout and IP validation, Solido’s new generative and agentic AI empowers engineering teams to achieve orders-of-magnitude productivity gains. It appears that Solido is leading the charge with the application of advanced agentic AI technology.

 A Growing Ecosystem 

As you would expect, successful deployments like this one facilitate expansion to other technologies in the ecosystem. At DAC, Siemens also announced support for NVIDIA NIM microservices and NVIDIA Llama Nemotron models. NVIDIA NIM enables the scalable deployment of inference-ready models across cloud and on-premises environments, supporting real-time tool orchestration and multi-agent systems. Llama Nemotron adds high context reasoning and robust tool-calling for more intelligent automation across the EDA workflow.  

To Learn More

The work Siemens presented at DAC was comprehensive, well thought out and widely adopted by development teams across the company. These are the elements of a very successful deployment of AI. It you’re thinking of adding AI to your design flow (and you should), you must learn more about what Siemens is up to. Here are some places to start:

• You can read the full press release here.
• You can learn more about Aprisa AI here.
• You can learn more about Calibre Vision AI here.
• You can learn more about Solido generative and agentic AI here.
• And you can get the big picture here.

And that’s how a new era of electronic design begins with Siemens EDA AI.