by Mark Fitzgerald | 09/05/2025
On September 4, 2025, Cadence Design Systems announced it would acquire Hexagon AB’s Design & Engineering (D&E) business for approximately $3.16 billion. The deal marks an important step in Cadence’s evolution, extending its focus beyond semiconductor design automation to embrace its broader ‘Intelligent System Design’ strategy.
This move significantly deepens Cadence’s footprint in structural and multibody dynamics simulation, adding capabilities that were traditionally the domain of independent simulation vendors. It also brings a strong customer base in automotive, including BMW, Toyota, and Volkswagen, as well as in aerospace and defense with BAE, Boeing, and Lockheed Martin.
Synopsys (NASDAQ: SNPS) executed one of the most dramatic shakeups in the simulation-EDA space with its $35 billion acquisition of Ansys (NASDAQ: ANSS) in mid-2025. This combination unites chip-design software with comprehensive multiphysics simulation, directly challenging Cadence’s broadened platform strategy.
Siemens (ETR: SIE), meanwhile, has solidified its role as a convergence leader. Earlier in March 2025, Siemens completed the acquisition of Altair Engineering for approximately $10 billion, integrating Altair’s advanced simulation, high-performance computing, and AI into its Xcelerator industrial software ecosystem.
These moves underscore a critical industry shift: EDA is merging with physical-world simulation. The integration of chip design, thermal and structural analysis, and AI-driven system modeling reflects customer demand for holistic, cross-domain engineering platforms.
Cadence’s serial acquisitions (first BETA CAE in 2024, now Hexagon’s D&E unit) parallel Synopsys’ Ansys integration. Together with Siemens’ long-standing EDA foothold, these companies are shaping the next era of digital engineering — where electronics, software, and physical systems converge in a single design ecosystem.
All three companies are reacting to the same market pressures. Modern systems are too complex to validate in silos. Electronics must be tested alongside mechanical structures and AI algorithms. Nowhere is this more urgent than in the verification of autonomous systems. Self-driving cars, drones and industrial robots must prove that their chips, sensors and control software will work safely in unpredictable real-world environments. Verification requires accurate digital twins that connect electronic design with structural analysis and AI-enhanced simulation.
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The study explores the rapidly evolving ecosystem of verification tools built for autonomous platforms. It assesses the capabilities and applications of top solutions, identifies emerging trends in simulation-based validation, and outlines best practices for achieving high-assurance autonomy.