As AI adoption surges in the U.S., memory and storage bottlenecks are bottlenecking performance. ScaleFlux's compute-in-storage architecture and scalable CXL memory solutions deliver a breakthrough in speed, efficiency, and cost—enabling smarter AI infrastructure across cloud, edge, and high-performance environments.
MILPITAS, Calif., June 30, 2025 /PRNewswire-PRWeb/ -- As worldwide deployment of artificial intelligence (AI) grows, a critical bottleneck is emerging: memory capacity and data movement. A recent report warns that traditional memory architectures—especially DRAM—are failing to keep pace with today's AI demands, consuming over 30% of data center power while limiting performance scalability and efficiency.(1)
To address this, ScaleFlux, a top innovator in data-centric infrastructure, has launched a next-generation architecture that embeds compute directly into the storage layer and supports advanced memory technologies via Compute Express Link (CXL). This design significantly improves throughput, reduces latency, and enables organizations to build AI systems that are not only faster—but also leaner, more efficient, and easier to scale.
"Every major AI breakthrough—from large language models to edge inferencing—depends on fast, intelligent data movement," said Hao Zhong, CEO of ScaleFlux. "What's needed isn't just faster chips—it's a smarter foundation. That's where we come in."
AI's Growing Demands Are Testing Legacy Infrastructure
AI is projected to contribute over $4 trillion annually to the global economy, with U.S. companies leading advancements across healthcare, manufacturing, finance, and beyond.(2) But these gains come at a cost: modern AI workloads are exceptionally data-hungry and latency-sensitive. Traditional DRAM and NAND-based systems can no longer keep up with the volume and velocity of data needed for AI model training and inference. Latency, I/O bottlenecks, and server resource constraints are inflating costs and energy consumption while slowing time-to-insight.
A New Approach to Compute, Memory and Storage
ScaleFlux's Compute + Storage Drive (CSD) 5000 series and FX5016 NVMe SSD controller offer a transformative alternative. By handling the taxing task of data compression with hardware engines in the drive controller—ScaleFlux drastically reduces I/O delays, minimizes CPU load, delivering high throughput without increasing power consumption or rack space.
Simultaneously, ScaleFlux's new MC500 CXL Memory Controller allows organizations to expand DRAM capacity over the PCIe bus—giving AI systems access to significantly more memory without costly server overhauls. CXL-based memory solutions improve reliability, availability, and serviceability (RAS), which are critical for running large-scale AI workloads efficiently.
This integrated architecture reduces the need to move data between isolated compute and storage silos—evolving the data pipeline for lowering latency, more efficient CPU utilization, and boosted real-world AI performance from the cloud to the edge.
Powering AI at Scale—Sustainably
With AI workloads poised to account for up to 9% of U.S. data center electricity demand by 2030, improving energy efficiency is no longer optional—it's a necessity for sustainable AI deployment.(3) By cutting redundant data transfers and minimizing CPU load, ScaleFlux's solutions not only increase performance but also reduce power consumption across training and inference cycles. That makes them particularly valuable in carbon-sensitive data centers and dense edge deployments—where power, space, and cooling are constrained but performance expectations remain high.
Real-World Impact Across AI Infrastructure
From cloud platforms to edge AI systems and high-performance computing (HPC), ScaleFlux's technology is helping organizations build smarter infrastructure for the AI era.
- Cloud and hyperscale teams are deploying CSD5000 series to reduce bottlenecks, improve data throughput, and lower total cost of ownership.
- AI and ML engineers gain faster access to large datasets, improving model training speed and inference responsiveness.
- Edge and HPC strategists use ScaleFlux to bring low-latency, high-efficiency processing closer to where data is generated—whether in factory floors, hospitals, or city infrastructure.
Early adopters are reporting tangible gains in performance, energy savings, and workload reliability. "We've engineered an architecture that cuts through legacy inefficiencies," Zhong added. "It's not about throwing more hardware at the problem—it's about making the hardware and the data pipeline smarter. That's how you scale AI sustainably."
Rethinking Infrastructure for AI's Next Phase
As AI reshapes nearly every industry, memory and storage will play an increasingly strategic role. Organizations that cling to conventional infrastructure face rising costs, energy constraints, and performance ceilings. Those who rethink the data layer will lead. With high-efficiency NVMe SSDs and scalable CXL memory solutions, ScaleFlux is building the foundation for AI systems that are faster, leaner, and built for what's next.
"AI's future won't be built on faster chips alone—it depends on smarter infrastructure that rethinks how data flows," said Zhong. "At ScaleFlux, we're laying the groundwork for more efficient, scalable, and future-ready AI systems."
About ScaleFlux
In an era where data reigns supreme, ScaleFlux emerges as the vanguard of enterprise storage and memory technology, poised to redefine the landscape of the data infrastructure - from cloud to AI, enterprise, and edge computing. With a commitment to innovation, ScaleFlux introduces a revolutionary approach to storage and memory that seamlessly combines hardware and software, designed to unlock unprecedented performance, efficiency, security and scalability for data-intensive applications. As the world stands on the brink of a data explosion, ScaleFlux's cutting-edge technology promises not just to manage the deluge but to transform it into actionable insights and value, heralding a new dawn for businesses and data centers worldwide. For more details, visit scaleflux.com.
References
1. ---. "Memory: The next Frontier for AI Performance - EE Times Europe." EE Times Europe, 7 Mar. 2025, eetimes.eu/breaking-through-memory-bottlenecks-the-next-frontier-for-ai-performance/.
2. Chui, Michael, et al. "Economic Potential of Generative AI | McKinsey." Mckinsey.com, 14 June 2023, mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier.
3. Shehabi, Arman, et al. 2024 United States Data Center Energy Usage Report. 2024.
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