This chip startup just raised $135M on a bet that AI’s biggest bottleneck isn’t compute – it’s memory XCENA, a startup with offices in South Korea and the U.S., has developed a new chip that places compute capabilities closer to DRAM, aiming to reduce the inefficiencies and high costs associated with data relay races in AI requests. The company recently raised $135 million in Series B funding to develop its MX1 chip, which processes data near memory to avoid costly round trips between CPUs, GPUs, and memory. If successful, this memory-centric approach could significantly lower AI infrastructure costs, with mass production of the MX1 chip scheduled for late 2026.

• XCENA is a startup aiming to solve the inefficiency and high cost of AI data processing by placing compute capabilities closer to memory (DRAM).
• The company’s new chip, the MX1, processes data directly within the memory module, reducing the need for data to travel between CPUs, GPUs, and memory.
• XCENA raised $135 million in a Series B funding round, bringing its total funding to $185 million.
• The startup’s founders are veterans of Samsung and SK Hynix, memory giants.
• XCENA’s thesis is that AI inference is increasingly a memory scaling problem, not just a compute problem.
• The MX1 chip connects to the CPU via CXL and handles tasks like preprocessing and KV cache management directly within the memory module.
• The company expects mass production of the MX1 chip by the end of 2026, with revenue generation starting in 2027.
• XCENA’s chip design uses thousands of small, efficient RISC-V cores and a high degree of vertical integration. Continue reading https://techcrunch.com/2026/05/29/xcena-secures-135m-at-570m-valuation-betting-on-memory-as-ais-real-bottleneck/