Cadence unveils its AuraStack AI Super Agent on Cadence Allegro AI Studio, an AI platform for printed circuit board (PCB) and advanced packaging design. The solution, accelerated by NVIDIA Blackwell and NVIDIA CUDA-X, coordinates domain-specific AI agents across planning, implementation, and tightly integrated Multiphysics analysis domains to compress the system-design cycle through manufacturing. Now, Cadence is the only provider with agentic AI solutions spanning the full electronic system design flow.
Cadence
Cadence introduces its AuraStack AI Super Agent
“The next era of AI infrastructure—spanning data centres, automotive, aerospace and physical AI—will be defined not only by silicon, but by the systems that connect, power and cool it,” said Michael Jackson, Corporate Vice President of R&D for System Design and Analysis at Cadence. “As hyperscale data centres deploy massive AI clusters and other industries advance increasingly intelligent, high-performance systems, engineering teams face growing complexity in PCB and advanced package design. Agentic AI orchestration, combined with trusted EDA and SDA tools, enables customers to move from manual iteration to intelligent, automated design realisation.”
Building on the same architecture as Cadence’s ChipStack AI Super Agent, agentic AI is combined with principled simulation and optimisation tools. The AuraStack AI Super Agent combines automation and optimisation for system planning, constraints management, physical structure definition, IP creation and reuse, place and route, design for manufacturability and multiphysics analysis across Cadence’s system design and analysis portfolio. It introduces a unified, AI-driven multiphysics foundation that concurrently models and optimises electrical, thermal and mechanical behaviour within a closed-loop environment. This enables real-time design convergence and boosts overall system reliability.
Key benefits of the AuraStack AI Super Agent include:
- Accelerating time to market by 2x, with 15x productivity and multiphysics-driven quality.
- Unifies separate engineering teams around a shared, multiphysics-aware design environment.
- Advances early and continuous multiphysics co-optimisation to reduce late-stage rework and expensive design iterations.
- Limits expensive re-spins by identifying system issues earlier in development.
- Enables product-level optimisation.
Cadence’s collaborations
NVIDIA is using Cadence to automate and optimise complex system design workflows for its engineering teams.
“The scale and complexity of modern AI infrastructure demands a new design approach,” said Tim Costa, Vice President and General Manager of Computational Engineering at NVIDIA. “NVIDIA's collaboration with Cadence is advancing AI-powered engineering workflows that accelerate design convergence and innovation across the industry. The Cadence AuraStack AI Super Agent and the Millennium M2000 Supercomputer deliver up to 20X faster multiphysics performance, giving our engineers the capability to tackle the most demanding design challenges and bring the next generation of AI infrastructure to life.”
Cadence is partnering with TSMC to help customers accelerate advanced package implementation through AI-driven automation. This will provide timely design convergence for increasingly complex multi-die systems.
“As advanced packaging complexity grows, customers need new levels of automation to achieve timely design convergence,” said Aveek Sarkar, Director of the Ecosystem and Alliance Management Division at TSMC. “Our long-standing partnership with Open Innovation Platform (OIP) ecosystem partners like Cadence to deliver advanced package design and verification solutions for TSMC 3DFabric technologies helps customers accelerate the realisation of next-generation multi-die systems for AI and high-performance computing applications. Through our multi-year collaboration on substrate auto routing, we are already enabling customers to boost productivity by 100X while delivering quality of results like manual routing.”
Cadence is helping Socionext to accelerate the automation and optimisation of complex semiconductor package and PCB design workflows.
“AI-driven agents are set to transform IC package and PCB design by automating SI, PI and thermal workflows and enabling generative design,” said Iwasaki Toshifumi, Lead Design Execution Leading Unit, Global Leading Group at Socionext Inc. “This acceleration allows our engineers to focus on higher-value work like architecture exploration, margin optimisation, and multiphysics trade-offs, while capabilities such as automated routing and chip-package-board co-design accelerate convergence and reduce manual effort.”
FORVIA HELLA is continuing to advance intelligent, sustainable mobility solutions.
“Working closely with Cadence has fundamentally changed the way FORVIA HELLA develops advanced automotive electronics. Using AI-assisted placement technology, a task involving the placement of 300 components that previously took up to four days can now be completed in just four minutes,” said Sven Hoenecke, President & CEO, Electronics NSA at FORVIA HELLA. “This step change in productivity allows our engineers to evaluate more design alternatives, optimise layouts earlier in the development process, and accelerate the development of innovative products without compromising quality. By automating repetitive work, our teams can focus more time on solving complex engineering challenges and bringing new technologies to market faster.”
Schneider Electric and Cadence are teaming up to apply AI-driven design automation and engineering expertise to accelerate electronic design workflows and scale institutional knowledge across engineering teams.
“At Schneider Electric, we see AI as much more than a productivity tool. Our collaboration with Cadence has demonstrated the potential of AI to accelerate design activities and improve engineer efficiency,” said Daniel Gheno, Senior Vice President, Innovation and Technology EM at Schneider Electric. “The next frontier is to combine design automation with engineering expertise, enabling companies to capture decades of know-how and make robust design decisions available to every engineer. We believe this is where AI can truly transform electronic design.”