XCENA Secures $135 Million in Series B Funding
XCENA, a Seoul-based company specializing in intelligent memory solutions, has announced a successful Series B funding round, raising $135 million. The investment was led by Altinum and IMM Investment, with participation from Corstone Asia, SBI Investment, and Mirae Asset Capital. The funding round took place on May 29, 2026.
Advancing Memory Solutions for AI
XCENA focuses on developing memory solutions based on Compute Express Link (CXL) technology. These solutions are particularly relevant for industries that handle large-scale data processing, including AI big data, vector databases, and DNA analytics. By integrating compute capabilities closer to DRAM, XCENA aims to reduce the inefficiencies in current AI data processing workflows.
In a typical AI operation, data must travel back and forth between memory and various processing units like CPUs and GPUs. This process can be a bottleneck, increasing costs and energy consumption. XCENA's technology seeks to streamline this by handling routine data operations near the memory, potentially transforming AI infrastructure.
Leadership and Vision
XCENA was co-founded by Jin Kim, Dohun Kim, and Harry Juhyun Kim in 2022, all of whom have backgrounds with tech giants Samsung and SK Hynix. CEO Jin Kim stated, "CPUs and GPUs have both gotten smarter over the decades. Memory never did. XCENA wants to change that."
Strategic Use of Funds
The newly raised capital will be directed towards scaling XCENA's operations and further developing its CXL-based memory solutions. This could involve expanding the team, enhancing product capabilities, and increasing market reach.
Investor Confidence
The substantial interest from investors underscores the growing recognition of memory as a critical component in the future of AI infrastructure. With the backing of major investment firms, XCENA is well-positioned to make significant strides in the industry.
This funding round marks a significant milestone for XCENA as it continues to advance its technology and address the challenges faced by AI and data-intensive industries.