Slide 1: Investor Day
_ synopsys INVESTOR DAY September 30, 2026
Slide 2: Tushar Jain
Tushar Jain Vice President, Investor Relations
Slide 3: Forward-Looking Statements and Non-GAAP Financial Information
This presentation contains certain forward-looking statements within the meaning of the federal securities laws, including, but not limited to, statements concerning our anticipated financial performance, guidance, long-term financial objectives and projections; anticipated synergies and other benef
Slide 4: Agenda
EASTERN TIME 1:00p – 1:05p Welcome & Agenda Tushar Jain Vice President, Investor Relations Sassine Ghazi 1:05p – 3:00p Synopsys' Next Phase of Growth President & Chief Executive Officer Joined by Shankar Krishnamoorthy Chief Product Development Officer 3:00p – 3:15p Break 3:15p – 3:45p Financial Mod
Slide 5: Sassine Ghazi
Sassine Ghazi President and Chief Executive Officer
Slide 6: 40 Years of Synopsys
Synthesis Based Design; ow te Desig Conpieles ou elo sin pace _40 Years _ of Synopsys
Slide 7: Pioneering the evolution from automated chip design to multi-domain systems engineering
Pioneering the evolution from automated chip design to multi-domain systems engineering The Scaling Era The SoC & IP Era The Pervasive Intelligence Era Enabling PCs & Enabling Mobile, Cloud & IoT Enabling SW-defined, AI-enabled Communications products everywhere 1980 1990 2000 2010 2020 2030 SILICON
Slide 8: 5 Years of Transformation by the Numbers
5 Years REVENUE & NON-GAAP OPERATI NG MARGIN 1,2 TRANS FO R MATIO N BY THE NUMBER S – FY22 – FY26E OUR EXPECTATIO NS EXITING THE YEAR ~$9.715B ~41.5% 2.1X 7+ Revenue Points of Non-GAAP $4.616B Growth3 Margin Expansion3 >22K 34.2% Customers Worldwide FY22 FY23 FY24 FY25 FY26E3 Revenue Non-GAAP Operat
Slide 9: #1 in Engineering Solutions
in Engineering Solutions From Silicon... ...to Systems ELECTRONIC DESIGN SIMULATION SILICON IP AUTOMATION (EDA) & ANALYSIS (S&A) #1 #1 #1 in EDA in Interface in Multiphysics S&A & Foundation IP
Slide 10: Era of Digital AI and Physical AI
Era of Digital AI Physical AI PURPOSE-BUILT SILICON
Slide 11: Silicon & Systems: Complexity, Pace, Cost
Silicon & Systems Complexity Pace Cost Compounding Accelerating Increasing First-time-right systems are critical
Slide 12: For the Era of Pervasive Intelligence
For the Era of Pervasive Intelligence
Slide 13: $1.7T Diversified & Resilient
Semiconductors Healthcare Rest of $1.7T High-Tech Diversified & Resilient Other Automotive & Transportation Aerospace & Defense
Slide 14: Increasing spend in technology tools to boost engineering productivity
$1.7T Increasing spend in …leads to saving in labor and technology tools to boost physical testing, avoiding engineering productivity and 10% 90% re-work and delays “shift left” product testing… in time-to-market SOFTWARE, IT INFRA & SERVICES ENGINEERING LABOR & PHYSICAL PROTOTYPES
Slide 15: Digital AI & Physical AI Expands our Opportunity
Digital AI & Physical AI Expands our opportunity SILICON SYSTEMS Compute demand drives design starts Systemic complexity of engineering & rise of application-optimized silicon intelligent products drives S&A demand PHYSICS-AWARE CO-DESIGN Autonomous Engineering Built on ground truth physics-based en
Slide 16: Expanding our opportunity, accelerating our growth
Expanding our opportunity, accelerating our growth
Slide 17: Design IP
Slide 18: Interface IP and Foundation IP
#1 #1 INTERFACE IP FOUNDATION IP Industry-leading IP spanning datacenter, Only IP provider mobile, automotive and consumer markets at leading-edge, Gate-All-Around nodes Silicon Proven: 10+ Foundries; 80+ Process Nodes; 3000+ IP Products
Slide 19: Data Center
ata Center Se
Slide 20: AI Rack
Slide 21: AI Server Blade
Al Server Blade »
Slide 22: Interface IP
Interface IP Pele DDR HBM Ethernet UCIE USB Foundation IP
Slide 23: Faster Pace Dictates a Recipe Change for AI Silicon
Annual AI silicon cycles are outpacing the standards progression INDUSTRY STANDARDS CHANGE EVERY 2-3 YEARS Protocol Ecosystem Broad Market Definition Development Adoption AI LEADERS DELIVERING A NEW PRODUCT EVERY 12 MONTHS Workload System Silicon Requirements Architecture Generation Faster Pace Dict
Slide 24: Custom AI accelerators growth and drivers
CUSTOM AI ACCELERATORS * DRIVERS ~$237B Supplier optionality ~6X Cost ~$37B Workload Efficiency 2025 2030
Slide 25: Hyperscaler custom silicon quotes
” ” ” Having our own hotly We are optimizing every We have been making demanded AI chip layer of the tech stack, strategic investments in opens up many from DC design to areas like our internal possibilities, but silicon to systems custom silicon effort perhaps none larger software, the model which
Slide 26: Standards Based IP: Factory 1
‘FACTORY 1’ Standards Based IP Build once, license broadly to 100s of customers
Slide 27: Application Optimized IP (AOIP): Factory 2
‘FACTORY 1’ ‘FACTORY 2’ EXPANSION Standards Based IP Application Optimized IP (AOIP) Build once, license broadly to Build optimized silicon with 100s of customers select customers
Slide 28: Factory 1 and 2 revenue: license and NRE fees
‘FACTORY 1’ ‘FACTORY 2’ EXPANSION Standards Based IP Application Optimized IP (AOIP) Build once, license broadly to Build optimized silicon with 100s of customers select customers $ License $ Nonrecurring Engineering (NRE) Fees
Slide 29: Factory 1 and 2 revenue: license, customization, royalty
‘FACTORY 1’ ‘FACTORY 2’ EXPANSION Standards Based IP Application Optimized IP (AOIP) Build once, license broadly to Build optimized silicon with 100s of customers select customers $ License $ License $ Nonrecurring Engineering (NRE) Fees $ Customization Fee $ Royalty
Slide 30: Standard vs AOIP development motion
STANDAR D AOIP CO-DESIG N WITH SYSTEM DEVELOPMENT MOTION ARCHITECTUR E & WORKLOADS Standard Defined Customer Workloads IP Co-design w/ Customer IP Developed Embedded Customer IP Integration into SoC Silicon Proven Engagement System Validation Licensed Broadly Production Repeatable • Scalable • Broad
Slide 31: Compute, ASIC, Connectivity
COMPUTE ASIC CONNECTIVITY AI accelerators and CPU Custom silicon suppliers Scale-up and Scale-out backbone
Slide 32: Amazon customer quote
” As our chip designs grow more ambitious and AI reshapes the engineering process itself, Synopsys help us move faster across the design cycle, helping us deliver more capable, efficient computing for customers ” worldwide. Peter DeSantis Senior Vice President, Amazon
Slide 33: Synopsys Enables the World's Foundries
Synopsys Enables the World’s Foundries
Slide 34: Multi-foundry capacity sourcing drives re-targets and new design starts
Multi-foundry capacity sourcing drives re-targets and new design starts Synopsys' silicon-proven catalog attaches at the new node without a re-architecture Foundries also buy enablement (NRE and license) Synopsys is the choice for IP across foundries and nodes.
Slide 35: TSMC customer quote
” Silicon-proven interface IP is one of the critical enablers of AI systems, unlocking the full potential of advanced logic and advanced package technologies. Synopsys is a key TSMC Open Innovation Platform® (OIP) IP Alliance partner, enabling our customers to rapidly realize next-generation AI syst
Slide 36: Synopsys and Intel
synopsys | intel
Slide 37: Synopsys and Samsung
SynOPsyS § SAMSUNG
Slide 38: AOIP projected to grow to ~$1B by FY30E
More design starts; more IP content AOIP projected to grow to ~$1B by FY30E Factory 2: Application Optimized IP Expansion (AOIP) Royalty upside grows over time Targeting royalty revenue mix > license fee over time Multi-Foundry Enablement
Slide 39: Design Automation: EDA
Design Automation: EDA WX
Slide 40: Silicon Architecture Complexity
GPT-6 Astra Frontier Claude Fable 5 Reasoning Frontier GPT-4.5/5 Reasoning 1e32 5-12T P Gemini Ultra 1-10M Tokens SILICON ARCHITECTURE COMPLEXITY* 1e30 1.5-2T P 1M Tokens 1e28 TRAINING COMPUTE (FLOP) GPT-4 1e26 GPT-3 1.8T P 175B P 128K Tokens 1e24 2K Tokens Heterogeneous Transformer Multi-Die System
Slide 41: Application Optimized IP and Multiphysics Signoff
Application Optimized Multiphysics IP Signoff High-Bandwidth System-level Memory Validation Advanced AI Packaging Engineering
Slide 42: Core EDA Platform and Multiphysics Fusion
CO R E G R O WTH CO R E EXPANS I O N MAR KET EXPANS I O N Core EDA Multiphysics Hardware-Assisted AI Platform Fusion Verification Platform Leading franchises, Agentic breadth & depth Signoff leadership accelerates Performance leadership for hyperconverged deliver scales engineering convergence faste
Slide 43: Innovation Vectors for the AI Era
INNOVATI O N VECTORS FOR THE AI ERA Agentic AI Automation PPA Leadership Multi-Die Optimized Multiphysics Fusion #1 FUSION COMPILER PRIMETIME VCS/VERDI PRIMESIM REDHAWK-SC 3DIC COMPILER Advanced-node leader; Undisputed Fastest digital GPU Power and thermal only exploration-to-signoff signoff leaders
Slide 44: Customer quote on custom AI inference accelerator
” Building a custom AI inference accelerator like Jalapeño requires turning ambitious architectural ideas into production silicon on an extremely compressed schedule. Synopsys' EDA solutions are instrumental to making that possible, helping engineering teams move from concept to silicon with the spe
Slide 45: Customer quote on AI product roadmap
” The success of our AI product roadmap depends on bringing increasingly complex silicon to market quickly and predictably. Synopsys' AI-powered EDA tools and Hardware platforms have proven essential for accelerating development, reducing execution risk, and achieving volume production faster across
Slide 46: Core EDA Platform and Multiphysics Fusion
CO R E G R O WTH CO R E EXPANS I O N MAR KET EXPANS I O N Core EDA Multiphysics Hardware-Assisted AI Platform Fusion Verification Platform Leading franchises, Agentic breadth & depth Signoff leadership accelerates Performance leadership for hyperconverged deliver scales engineering convergence faste
Slide 47: 3D, 2.5D, 2D multiphysics complexity
3D 2.5D 2D Stress Warpage Power/Signal Integrity >28nm Electro- Thermal Magnetics 22nm Photonics 16/14nm 10nm 7nm 5nm 3nm 2nm/18A 14A <10A
Slide 48: Evolution to Multiphysics Fusion
Pre 2016 2018 ANGSTROM ERA 2018-2023 AI SUPERCHIPS ERA 2026 Fusion Superior PPA, Convergence for Separate Tools Multiphysics Fusion with Architecture for Angstrom Era Rapid integration with Value Links Ground Truth Engines Hyperconvergence of New Functions Analog Power/Signal Stress ECO Formal Integ
Slide 49: Multiphysics Fusion solutions
ANALOG & I M P L E M E NT A T I O N M U L TI - D I E D E S I G N S SIGNOFF DESIGN CLOSURE P H O T O N I CS Faster convergence, Concurrent multiphysics Greater accuracy with Faster closure with IR- High-accuracy better PPA with power analysis through signoff SPICE-accurate IR and aware ECO optimizati
Slide 50: Multiphysics Fusion results since launch
IMPLEMENTATION MULTI-DIE SIGNOFF DESIGN CLOSURE ANALOG & PHOTONICS TOP CONSUMER ELECTRONICS PROVIDER 80% reduction >6x speedup Better silicon 5x faster design closure Up to 5-10x photonics layout in IR drop violations accuracy Up to 86% IR fix rate productivity 76% reduction 33% lower IR drop 4% Pes
Slide 51: Core EDA Platform and Multiphysics Fusion
CO R E G R O WTH CO R E EXPANS I O N MAR KET EXPANS I O N Core EDA Multiphysics Hardware-Assisted AI Platform Fusion Verification Platform Leading franchises, Agentic breadth & depth Signoff leadership accelerates Performance leadership for hyperconverged deliver scales engineering convergence faste
Slide 52: Pre-Silicon Validation Is Essential
AI CHIPS DOUBLE IN COMPLEXITY EVERY YEAR A LEADING-EDGE RESPIN CAN COST UP TO $100M* SOFTWARE VALIDATION COMPLEXITY HAS CROSSED A QUADRILLION CYCLES Pre-Silicon Validation Is Essential
Slide 53: ZeBu customer quote
” We're competing in one of tech's fastest-moving markets, where every month matters. Synopsys ZeBu emulation solution enabled us to validate our chip in context of AI inference workloads pre- silicon. As a result, we brought our production chips up and ran AI inference workloads just weeks after re
Slide 54: ZeBu Server, ZeBu-200, EP-Ready HAPS
ZeBu® Server 5 ZeBu ® -200 12F EP-Ready HAPS ® 200 UNMATCHED CAPACITY SYSTEM-LEVEL PERFORMANCE SOFTWARE-DEFINED HAV Reliably validate the Validate the full system Increase performance over the system largest AI systems before silicon lifetime through software updates
Slide 55: Next Generation ZeBu Capacity and Performance for the AI Era
Next Generation ZeBu Capacity And Performance For The AI Era COMING IN 1H’27 Unmatched Larger Higher Reliability Capacity Performance & TCO
Slide 56: Core EDA Platform and Multiphysics Fusion
CO R E G R O WTH CO R E EXPANS I O N MAR KET EXPANS I O N Core EDA Multiphysics Hardware-Assisted AI Platform Fusion Verification Platform Leading franchises, Agentic breadth & depth Signoff leadership accelerates Performance leadership for hyperconverged deliver scales engineering convergence faste
Slide 57: Shankar Krishnamoorthy
Shankar Krishnamoorthy Chief Product Development Officer
Slide 58: Silicon & Systems: Complexity, Pace, Cost
Silicon & Systems Complexity Pace Cost Compounding Accelerating Increasing First-time-right systems are critical
Slide 59: Chip Design Engineers shortage and AI upside
350 330 Designer Shortage (Hyperscalers + AI Labs) 310 Designer Shortage (Merchant AI Supercycle) AI Upside Chip Design Engineers ('000) 290 Designer Shortage (Pre-AI) AI adds ~48K human Designer Supply equivalents by 2030, just 270 enough to bridge the pre- AI Supply (AI Tools + Agents) 250 AI shor
Slide 60: Copilots, task-level agents, orchestrated agents
LONG-HORIZON AGENT COPILOTS TASK-LEVEL AGENTS ORCHESTRATED AGENTS WORKFLOWS PROMPT PR OMPT PROMPT OU T COME Design EDA Data Execution EDA Execution RESU LT S EDA Design Execution Data Coverage Debug Agents Agents RESPONSE R ESPONSE RESPONSE Assist Execute Iterative, Autonomous Execution Autonomous E
Slide 61: Synopsys Agentic AI Portfolio
Synopsys Agentic AI Portfolio Delivering Breadth and Depth of AgentEngineer Solutions Verification Implementation AMS Manufacturing Meshing Blaze EMC Customer Agents AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM (Open Ecosystem
Slide 62: Synopsys AgentEngineer in Action
nopsys AgentEngineer™ in Action i Sy
Slide 63: With and without AgentEngineer
WITHOUT AGENTENGINEER WITH AGENTENGINEER VCS/VERDI Multiple VCS/VERDI licenses VCS/VERDI 1 license VCS/VERDI Agent 1 Job 1 VCS/VERDI Multiple VCS/VERDI VCS/VERDI 1 license licenses Job 2 5-10x Agent 2 VCS/VERDI More Tool VCS/VERDI Calls* VCS/VERDI 1 license Multiple VCS/VERDI licenses Job 3 VCS/VERD
Slide 64: 50+ Customer Engagements Underway
” 50+ Customer Engagements Underway ” Our work with Synopsys Verification AgentEngineer technology Synopsys is combining its silicon-to-systems expertise with highlights the promise of agentic AI for debug…We believe these NVIDIA accelerated computing and NVIDIA Agent Toolkit, advancements can help
Slide 65: AI Monetization Framework
Al Monetization —. Framework \
Slide 66: Agent and human tool usage
AGENT HUMAN TOOL USAGE TOOL AGENT USAGE HUMAN TOOL USAGE TOOL USAGE HUMAN TOOL USAGE
Slide 67: Multiple paths to monetization
Synopsys’ Strategy Provides Customer Optionality and Multiple Paths to Monetization Synopsys Customer-Owned Frontier Full Stack Platform Models + Agents EDA and S&A Engines Provide Physics-Based Ground Truth
Slide 68: Synopsys Full Stack
Verification Implementation AMS Manufacturing Meshing Blaze EMC Customer Agents AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM (Open Ecosystem) LONG- Synopsys HORIZON AGENTS Full Stack TASK Coverage Closure PPA Closure Analog De
Slide 69: Customer-Owned Platform Agents
Customer Platform Synopsys AutopilotTM Platform Customer Agents Verification Implementation AMS Manufacturing Meshing Blaze AgentEngineer EMC AgentEngineer (Open Ecosystem) TM AgentEngineer AgentEngineer AgentEngineer AgentEngineer TM TM TM AgentEngineer TM TM TM Customer-Owned Platform + Agents … A
Slide 70: Training Frontier Models and Using Frontier Models
Training Using Frontier Models Frontier Models Tool Subscription / Consumption Tool Subscription Revenue Share
Slide 71: Synopsys and OpenAI: GPT-Synopsys
Synopsys | OpenAl ANNOUNCING GPT-Synopsys How to revolutionize chip design?
Slide 72: Specialized Frontier Model
SPECIALIZED OPTIMIZE, ENGAGEMENTS FRONTIER MODEL VERIFY, & DELIVER UNDERWAY Built using OpenAI intelligence Improved outcomes for complex With leading and Synopsys' trusted EDA tools, silicon designs, faster semi customers agents and expertise
Slide 73: Ground Truth EDA Engines
Ground Truth EDA Engines Agentic AI Built Over Decades Verified Outcomes Foundry-certified Signoff • Deterministic • Physics Grounded • Rigorously Better PPA • Faster Closure • Reason • Plan • Orchestrate • Execute Validated • Manufacturing/Yield Assurance Higher Engineering Capacity EDA FOUNDRY “In
Slide 74: EDA growth drivers
More complex silicon & design starts Convergence of electronics & physics AI-driven chip design
Slide 75: Design Automation: Simulation & Analysis
Design Automation: Simulation & Analysis
Slide 76: Faster than engineering teams can respond
Faster than engineering teams can respond Of components redesigned Of new product offerings Of manufactured products before production exceed cost targets expected intelligent / connected
Slide 77: Digital Engineering Shift Drives Durable S&A Growth
Digital Engineering Shift Drives Durable S&A Growth, with AI Reshaping Product Design Data Centers Robotics Aerospace Industrial Chip-to-chillers end-to-end Sim-to-real validation & Digital test ranges and Digital twins for operational system optimization. synthetic data generation. mission simulati
Slide 78: Many expensive prototypes and costly product failures
REQUIREMENTS DESIGN SIMULATION BUILD TEST 100s Simulations Many expensive prototypes & many costly product failures
Slide 79: 1000s Simulations
REQUIREMENTS DESIGN SIMULATION BUILD TEST 1000s Simulations
Slide 80: Headlamp performance with 80% fewer physical iterations
Shortened development cycles, Achieved optimal headlamp reduced physical testing, and Scaled from a few specialists to performance with 80% fewer enabled better engineering hundreds of engineers adopting physical development iterations decisions throughout the product simulation transforming product
Slide 81: Digital Engineering connects Data, People and Processes
FLUID DYNAMICS STRUCTURAL ELECTROMAGNETICS OPTICAL THERMAL ANSYS FLUENT ANSYS MECHANICAL ANSYS HFSS ANSYS LUMERICAL ANSYS ICEPAK Best-in-class Multiphysics and Broadest Simulation Signoff Portfolio Ground truth physics solvers Digital Engineering connects Data, People and Processes, improving Produ
Slide 82: Ground truth physics-based signoff is essential
REQUIREMENTS DESIGN SIMULATION BUILD TEST DEMOCRATIZATION OF SIMULATION AI DRIVEN INFLECTION simAI & optiSLang MESHING AGENTENGINEER BLAZE AGENTENGINEER EMC AGENTENGINEER SURROGATE MODELS AGENTS FRONTIER MODELS Ground truth physics-based signoff is essential for every stage.
Slide 83: Democratization of simulation
REQUIREMENTS DESIGN SIMULATION BUILD TEST DEMOCRATIZATION OF SIMULATION AI DRIVEN INFLECTION simAI & optiSLang SURROGATE MODELS Ground truth physics-based signoff is essential for every stage.
Slide 84: AI driven inflection in simulation
REQUIREMENTS DESIGN SIMULATION BUILD TEST DEMOCRATIZATION OF SIMULATION AI DRIVEN INFLECTION simAI & optiSLang MESHING AGENTENGINEER BLAZE AGENTENGINEER EMC AGENTENGINEER SURROGATE MODELS AGENTS FRONTIER MODELS Ground truth physics-based signoff are essential for every stage.
Slide 85: Synopsys Agentic AI Portfolio
Synopsys Agentic AI Portfolio Delivering Breadth and Depth of AgentEngineer Solutions Verification Implementation AMS Manufacturing Meshing Blaze EMC Customer Agents AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM AgentEngineer TM (Open Ecosystem
Slide 86: Democratizes Simulation Usage Across Product Development
AI POWERED SIMULATION REQUIREMENTS DESIGN BUILD TEST Democratizes Simulation Usage Across Product Development
Slide 87: Digital Twin
Datacenter Industrial Datacenter Automotive Space Construction HVAC and digital High-speed filling Power management & Lighting and optical Lunar landers and space Construction infrastructure operations digital twins design systems component digital twins Semiconductor Industrial Automotive Robotics
Slide 88: S&A growth drivers
More simulation, digitization of design Value capture, accelerated simulation More users, AI driven inflection New opportunities, digital twins
Slide 89: Long-Term Growth Outlook and FY27 Outlook
LONG-TERM GROWTH OUTLOOK FY27 OUTLOOK (MIDPOINT OF RANGE) Total Revenue Total Revenue Mid-Teens CAGR ~$11.15B FY26E – FY30E Revenue CAGR ~15% ~15% YoY Growth
Slide 90: Digital AI & Physical AI Expands our Opportunity
Digital AI & Physical AI Expands our opportunity SILICON SYSTEMS Compute demand drives design starts Systemic complexity of engineering & rise of application-optimized silicon intelligent products drives S&A demand PHYSICS-AWARE CO-DESIGN Autonomous Engineering Built on ground truth physics-based en
Slide 91: Thank You
SYNOPSys’ Thank YJ
Slide 92: Shelagh Glaser
Shelagh Glaser Chief Financial Officer
Slide 93: Why Now, Why Us
WHY NOW WHY US INFLECTION POINT UNMATCHED ASSETS & SCALE • Pace & complexity of silicon • #1 portfolio; Silicon proven and systems solutions at scale • Ground truth physics-based solvers and engines CUSTOMER NEEDS LEADING THE INDUSTRY • Application optimized, first • Higher value capture with time r
Slide 94: 5 Years of Transformation by the Numbers
5 Years REVENUE & NON-GAAP OPERATI NG MARGIN 1,2 TRANS FO R MATIO N BY THE NUMBER S – FY22 – FY26E OUR EXPECTATIO NS EXITING THE YEAR ~$9.715B ~41.5% 2.1X 7+ Revenue Points of Non-GAAP $4.616B Growth3 Margin Expansion3 >22K 34.2% Customers Worldwide FY22 FY23 FY24 FY25 FY26E3 Revenue Non-GAAP Operat
Slide 95: FY26E Execution
FY26E Execution 1 N O N - G A AP N O N - G A AP FREE R E V E N UE O P E R AT I N G M A R G I N 3 EPS3 CASH FLOW3 CURRENT GUIDE 2 CURRENT GUIDE CURRENT GUIDE CURRENT GUIDE ~$9.715B ~41.5% ~$15.07 ~$2.6B
Slide 96: Revenue by product group: current and FY27
F Y 2 6 — C U R R E N T R E V E N U E B Y P R O DU C T G R O UP F Y 2 7 — N E W R E V E N U E B Y P R O DU CT G R O U P ED A EDA DESIGN AUTOMATION DESIGN AUTOMATION SCBU INCLUDING: ANSYS SCBU + OTHER OTHER A NS Y S S&A (Simulation and Analysis) SCBU (Semiconductor Business Unit) O T HER SIMULATION &
Slide 97: FY26E-FY30E Revenue CAGR
FY26E-FY30E Revenue CAGR 1 DESIGN AUTOMATION SEGMENT DESIGN IP SEGMENT EDA S&A DESIGN IP Mid-Teens Double-Digit High-Teens F Y 2 6 E - F Y3 0 E F Y 2 6 E R E V E NU E O B J E C TI V E (MIDPOINT)2 Growth Growth Growth 13%+ 10%+ 17%+ Mid-Teens ~$9.715B CAGR ~15% R E V E N UE S Y N E R G I E S V A L U
Slide 98: Revenue and cost synergies
1 REVENUE SYNERGIES ON TRACK How We Get There ACROSS EDA & S&A ~$400M Multiphysics Fusion Systems Expansion run-rate by FY29E FY25 FY26E FY27E FY28E FY29E 1 A C C E L E RA T E D COST SYNERGIES ~1 YEAR FASTER ~$400M ORIGINAL PLAN Source Of Savings ~$400M run-rate by FY28E run-rate by FY27E Streamlini
Slide 99: Operating margin expansion to ~50% by FY30E
~50% ~+850bps ~41.5% FY26E FY30E
Slide 100: Scale and efficiency driving margins
~50% SCALE & EFFICIENCY DRIVING MARGINS Value Capture Portfolio Optimization ~+850bps Operational Leverage WHERE WE'RE INVESTING ~41.5% Advanced-Node & Multi- Simulation & Digital Die Design Engineering Application Optimized IP AI for Engineering (Factory 2) FY26E FY30E
Slide 101: Capital allocation priorities
1 Invest for Growth R&D First Fund organic innovation & disciplined M&A 2 Maintain a Strong Balance Sheet Maintain Investment Grade Rating Term loans fully repaid ahead of schedule 3 Return Capital to Shareholders Up to 50% of FCF Planned return to shareholders via share repurchases through FY30E
Slide 102: SBC as % of revenue
SBC AS % OF REVENUE 1 12.7% 12% ~9.8% ~9% ~8% 8% of revenue by FY30E 4% 0% FY25 FY26E FY27E FY30E
Slide 103: Non-GAAP EPS and Free Cash Flow
Non-GAAP EPS2 FREE CASH FLOW2 ~$35 $35.00 $6.0B ~$6B $30.00 $5.0B Mid 20%s $25.00 CAGR Mid 20%s Free Cash Flow ($B) Non-GAAP EPS ($) FY26E-FY30E $4.0B CAGR FY26E-FY30E $20.00 ~$15.07 $3.0B ~$2.6B $15.00 $12.91 $2.0B $10.00 $1.3B $5.00 $1.0B $0.00 $0.0B FY25 FY26E FY30E FY25 FY26E FY30E
Slide 104: The Value Equation: long-term objectives
Through FY30E THE VALUE EQUATION Revenue Growth + Margin Expansion + Capital Allocation = EPS & FCF Growth 1 LONG TERM OBJECTIVES REVENUE NON-GAAP NON-GAAP EPS FREE CASH FLOW CAPITAL RETURN3 2 2 2 GROWTH OPERATING MARGIN GROWTH GROWTH Mid-Teens ~50% Mid 20%s Mid 20%s Up to 50% ~15% FY26E–FY30E CAGR
Slide 105: Long-Term Model to The Year Ahead
LONG-TERM MODEL → THE YEAR AHEAD
Slide 106: FY27 guidance midpoints
Midpoints of Range 1 REVENUE NON-GAAP NON-GAAP EPS OPERATING MARGIN 1 ~$11.15 B ~44.0% ~$19.08 ~15% Growth YoY2 ~+250 bps YoY2 ~27% Growth YoY2 Range: $11.1B - $11.2B Non-GAAP Expense Range: $6.215B - $6.275B Range: $19.04 - $19.12
Slide 107: Margin expansion FY25-FY27E
FY25-FY27E 1,2 +670 bps of margin expansion in two years driven by revenue growth, value capture and operating leverage ~44.0% ~+250bps ~41.5% ~+420bps 37.3% FY25 FY26E FY27E
Slide 108: FY26E and FY27E guidance summary
Continued growth with meaningful margin and FCF expansion METRIC FY26E GUIDANCE 1,2 FY27E GUIDANCE 1,2 Revenue ~$9.715B ~$11.150B Non-GAAP operating margin ~41.5% ~44.0% Non-GAAP EPS ~$15.07 ~$19.08 Fully Diluted Outstanding ~193M ~191M Shares Free cash flow ~$2.6B ~$3.1B
Slide 109: Intent to repurchase shares over coming months
INTENT TO REPURCHASE SHARES OVER COMING MONTHS1 O FFS ET DI LUTI O N R EDUCE S HAR E CO UNT I NCR EAS E EPS Enabled by Stronger Cash Generation, Margin Expansion and Continued Deleveraging
Slide 110: Thank You
SYNOPSYS’ hank You \ x
Slide 111: Appendix: Non-GAAP Reconciliations, Definitions and FY27 Detailed Guide
Hor t Non-GAAP Reconciliations, Definitions d FY27 Detailed Guide
Slide 112: Forward-looking non-GAAP financial measures
This presentation contains certain forward-looking financial measures that are not in accordance with the U.S. generally accepted accounting principles (“GAAP”). It also includes future estimates for non-GAAP operating margin, non-GAAP tax rate, non-GAAP interest and other income (expense), net, non
Slide 113: Operating income and operating margin
Operating income and operating margin 2 2 2 3 3 ($ IN MILLIONS) FY2022 FY2023 FY2024 FY2025 FY2026E FY2027E Revenue $4,615.7 $5,318.0 $6,127.4 $7,054.2 ~$9,715 ~$11,150 GAAP operating income and operating margin $1,148.7 24.9% $1,273.2 23.9% $1,355.7 22.1% $914.9 13.0% ~10.4% ~20.7% Adjustments: Amo
Slide 114: Net income per diluted share (EPS)
Net income per diluted share (“EPS”) 1 1 PER DILUTED SHARE FY2025 FY2026E FY2027E GAAP net income per diluted share attributed to Synopsys $8.07 $3.96 $8.39 Amortization of acquired intangible assets $3.04 $8.36 $8.09 Stock-based compensation $5.39 $4.93 $5.08 Acquisition/divestiture related items (
Slide 115: Free cash flow reconciliation
($ IN MILLIONS) FY2025 FY2026E FY2027E Cash flow from operating activities $1,519 ~$2,800 ~$3,600 ( - ) Purchases of property and ($169) ~($225) ~($500) equipment = Free Cash Flow $1,350 ~$2,600 ~$3,100
Slide 116: FY27 guidance: expenses
FY27 guidance: expenses ($ IN MILLIONS) FY2027E MIDPOINT FY2027E LOW FY2027E HIGH Target GAAP expenses $8,835 $8,765 $8,905 Adjustments: Amortization of acquired intangible assets ($1,545) ($1,540) ($1,550) Stock-based compensation ($970) ($960) ($980) Restructuring charges ($75) ($50) ($100) Target
Slide 117: FY27 guidance: net income per diluted share
FY27 guidance: net income per diluted share (“EPS”) PER DILUTED SHARE FY2027E MIDPOINT FY2027E LOW FY2027E HIGH Target GAAP net income per diluted share attributed to Synopsys $8.39 $8.16 $8.61 Adjustments: Amortization of intangible assets $8.09 $8.12 $8.06 Stock-based compensation $5.08 $5.13 $5.0
Slide 118: FY27 Guidance Metrics
METRIC 2027 Guidance1 Revenue ($M) $11,100 – $11,200 GAAP Expenses ($M) $8,765 - $8,905 Non-GAAP Expenses ($M) $6,215 – $6,275 Non-GAAP Interest and Other Income (Expense), Net ($M) ($465) – ($455) Non-GAAP Tax Rate 18% Fully Diluted Outstanding Shares (M) 190 – 192 GAAP Operating Margin Midpoint: ~
Slide 119: Investor Day
_ synopsys INVESTOR DAY September 30, 2026