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Applied Materials and Besi expand packaging partnership for AI chips

October 1, 2026 9:00 AM

Applied Materials, Inc. (Nasdaq: AMAT) and BE Semiconductor Industries N.V. (Euronext Amsterdam: BESI) announced an expansion of their strategic partnership, with Besi joining Applied's EPIC Center as an Innovation Partner, according to a press release issued Oct. 1, 2026.



The two companies first established a joint Center of Excellence at Applied's Advanced Packaging Development Center in Singapore in 2020, focusing on hybrid bonding technology. That collaboration produced Kinex, described as the first integrated die-to-wafer hybrid bonding system.



The expanded partnership will extend co-development beyond die-to-wafer hybrid bonding to include new hybrid bonding platforms, thermo-compression bonding, and die-on-wafer, die-on-die, and die-on-panel integration architectures. Photonics-enabled interconnect applications are also included in the planned R&D scope.



Besi engineers will work alongside Applied Materials teams at the EPIC Center in Silicon Valley. Applied has said capital spending on the EPIC Center is expected to reach approximately $5 billion as customer projects commence, representing what the company describes as the largest U.S. investment in semiconductor equipment and process technology R&D. The center is expected to be operationally ready in 2026.



"With Besi joining EPIC as an Innovation Partner, we're extending that collaboration across the interconnect technologies our customers need to scale AI systems," said Gary Dickerson, President and CEO of Applied Materials.



Richard Blickman, CEO and Chairman of the Board of Management of Besi, said joining the EPIC Center "is a natural next step, giving us a seat alongside the leading logic, memory and systems companies as we advance TCB scaling, die-on-panel integration and the interconnect technologies that will define the next generation of AI and photonics systems."



The partnership targets 3D IC scaling and logic and memory integration for AI compute and memory architectures, with the goal of giving shared customers earlier access to co-developed process and assembly solutions.

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