Synopsys Inc Investor Day 2026

Today's program is being recorded and webcast live. Please welcome Tushar Jain, Vice President Synopsys Investor Relations.

Thank you. Thank you, everyone. Good afternoon, and welcome to Synopsys' Investor Day. We're so glad to have you here. It's great to see so many familiar faces in person rather than on Zoom. It's a very exciting day for all of us here at Synopsys, and we thank you for joining us in person and for those joining us online. Before I go any further, I need to read a short legal disclosure. Synopsys will discuss forecasts, targets, and other forward-looking statements during today's presentation. While these statements represent our best judgment as of today, they are subject to risks and uncertainties that could cause actual results to differ materially. Important factors that may affect our future results are described in our most recent SEC filings.

We will refer to certain non-GAAP financial measures throughout today's presentation, and reconciliations to their most directly comparable GAAP financial measures can be found in the appendix section. A replay of today's event and the presentation materials will be available on our website at www.synopsys.com. All right. With that out of the way, as I said, we have an exciting agenda lined up today. Sassine is going to cover Synopsys' next phase of growth. You're going to hear from many of our customers, and then Shankar is going to join him on stage and go deeper into our AI platform. Following that session, we'll take a short break, and then Sheila's going to come on stage and put all of that in the context of our financial model. We'll end the day with a Q&A session. With that, let's get started.

This is the moment. AI is moving beyond the digital world and deeper into the physical one. Pervasive intelligence enabling innovators to build more efficiently, transform mobility, reach further, save more lives. Plus extraordinary advancements that will soon make the leap from imagination to reality. As the demands of AI increase, so does design complexity. But conventional engineering design workflows can't meet the challenges of what comes next, so the world turns to engineers. Engineers, they turn to Synopsys because we are re-engineering engineering. Advancing the design of physical AI. Intelligent systems so complex you can't build them without co-design and simulation. Welcome to the new agentic workflows for designing the AI future, where hardware and software, electronics and physics, silicon and systems are co-optimized. Where digital twins transform simulation, revealing how every part of a system will behave even before development has started.

And where silicon IP simplifies your design, moving you to market faster. From advanced silicon to intelligent systems, Synopsys removes the barriers between concept and deployment, enabling fearless innovation, unlocking bolder AI, and helping humanity build things it has never built before. At Synopsys, our mission is to empower innovators to drive human advancement.

Come myself. Hello, and welcome to Synopsys Investor Day. I cannot be more excited to be here in New York City with our shareholders and many who are joining us online. Before I get started, I want to send special shout-out to our employees. I know you've been anticipating this day as much as our shareholders, and I cannot thank you enough for the trust in the strategy, the agility and courage to act and shape the future of our company and delivering with excellence. So thank you. I cannot be more humbled to be part of this company. In my presentation today, I want to talk about the what is changing around us and the why and how Synopsys is positioned to maximize this opportunity. This year is a special year for Synopsys.

It's our 40th year anniversary, and it's very hard for companies for 40 years to start with a disruptive technology synthesis and maintain the leadership position, all anchored with staying on the leading edge of innovation and delivering the technology that our customer must have in order to deliver the best product that they are designing. The other important milestone for us this year is the year one of the new Synopsys, of the fully integrated Ansys and Synopsys. So we're very thrilled to celebrate our 40th year anniversary, as well as our new company. Over the last 40 years, we were able to deliver to our customers with different eras of technology disruption, innovation that was necessary, and we became mission-critical to our customers' success in delivering these differentiated products. In the era of pervasive intelligence The need to go beyond the silicon innovation to silicon to system is a necessity because the optimization cannot happen at one level of the stack.

It has to happen at the entire stack, from silicon to systems. Over the last five years, we've been on a mission to transform the company. Five years ago, Aart entrusted me as the President, then CEO, to lead the next chapter of Synopsys. During this time, with discipline and courage, we've been able to make number of portfolio decisions with divestitures of assets that we did not feel they were needed to deliver from silicon to system, or they were not the right asset for Synopsys to hold. At the same time, we opened up our balance sheet and acquired one of the most essential assets for the physical AI era.

When I say physical AI, that same asset, Ansys, is necessary to advance the chip design process as electronics and physics are merging. When we talk about Synopsys as the leader in engineering solutions from silicon to systems, it is very rare for companies to have three parts of their portfolio, and each part holds the number one leadership position in its market segment. We are the number one in EDA, in silicon IP, and simulation and analysis, or, as we call it, SNA. These assets are becoming critical as we envision the world, as we envision the future, the future products, as digital AI and physical AI are converging. The one common thing to drive the digital AI and physical AI is advanced silicon.

You are going to hear me talk repeatedly and more and more about purpose-built silicon, because the world of just a generic merchant off-the-shelf silicon is not going to deliver the efficiency required and needed in order for the workload and the applications to be optimized all the way along the stack. That optimization is needed and necessary in order to drive the right cost, the right competitiveness of the product. When we think about silicon to system and the increased complexity, pace, and cost of these designs, the need to co-design becomes a must. What does co-design mean in engineering? It means you are optimizing in one domain and having the adjacent domain taken into account, so you are not building too much margin in your product. That is what Synopsys is thriving to do. That is what we call we are re-engineering engineering in this era of pervasive intelligence.

How do we bring the portfolio together to enable our customers to build the most differentiated product with the lowest cost, on time, high-fidelity product with our portfolio? When we talk about co-design and digital twinning and modeling of the end product, it is all to deliver better, faster, cheaper products for our customers. We serve a global R&D spend of $1.7 trillion. If you look at the various industries on this chart and the dollar they invest in R&D in order to build their products, this is where Synopsys' opportunity comes in. About 90% of that $1.7 trillion leans on traditional way of building a product, physical prototyping. Only 10% of that $1.7 trillion is using technology in order to build their differentiated product.

The trend over the last five years, more money is coming towards the technology, and that 10% portion of the pie is growing, just simply driven by the complexity of these products. You cannot build an EV or a robot or a drone or a chip by having a physical prototype. You need to virtualize, model, design, simulate before you build and test. That is the opportunity we have, and we truly cannot be more excited about having our strategy as AI is transforming engineering from silicon to systems and expand our opportunity. At the silicon level, more chips are required to drive this intelligence and to compute for this intelligence. These chips are increasingly becoming application-optimized silicon, custom silicon, and it is evident by the number of OEM and system companies are trying to invest in building their own silicon.

The reason I am saying trying to invest, it is not easy to build the most advanced silicon to support the AI and the system requirements. At the system level, these systems are becoming more intelligent, AI-driven, a lot of software. The increased demand for simulation and analysis before you spend the money to build the physical prototype is becoming as well a necessity, and more important. The physics-aware co-design crosses silicon and system. On the chip level, the need to have physics simulation with electronics, and physics can be fluid, structure, thermal into electronics is already happening. At the system level, having the representation of physics as your end product operating in the real world is another driver as we move into physical AI. The one thing that we are very excited about is the opportunity that AI is bringing.

On Monday, and Shankar will talk about it more, we announced our AI platform, where we have in multiple areas and domains, an agent engineer that is able to call many of the sub-agents and the tools to perform tasks autonomously. That is only possible if you can trust the results of what the agents are producing. First-time right product is essential. In order to build a first-time right product, you need a trust in physics as these agents are generating output and outcomes. Now let us jump into the actual business, and given the tailwinds, how is Synopsys capturing these opportunities? I will go over the EDA, SNA, and design IP. As you know, we have two segments. Sheila will talk more about the segments that we have, which is design automation and design IP. I am going to start with IP.