TAIPEI, June 2, 2026 /PRNewswire/ -- Solid State Storage Technology Corporation (SSSTC), a subsidiary of Kioxia Corporation and a leading global SSD provider, is showcasing its enterprise SSDs designed for immersion cooling and engineered for AI-driven data centers, along with a comprehensive portfolio of industrial and enterprise SSD solutions.
As generative AI and high-density computing evolve, thermal management is critical. To address this, SSSTC has optimized its SSDs for immersion cooling environments by enhancing corrosion resistance through specialized materials, component protection, and structural design. The lineup includes the SATA ER3, ER4, and ER5 series, as well as the PCIe® U.2 PJ1 and EJ5 series.
These SSDs are optimized for immersion cooling environments, where systems are submerged in non-conductive dielectric fluids. By leveraging the high heat capacity and convective properties of liquids, heat can be efficiently dissipated through fluid circulation and heat exchange. This approach reduces reliance on traditional air cooling while improving Power Usage Effectiveness (PUE) and overall system reliability.
SSSTC is also highlighting a range of industrial and enterprise SSDs optimized for AI and edge applications. Industrial SSDs support Edge AI and harsh environment deployments, with operating temperatures ranging from -40 °C to 85 °C, along with anti-vibration and shock-resistant designs for outdoor and industrial environments. The pSLC architecture enhances endurance for sustained write-intensive workloads, while a multi-tier PLP (Power Loss Protection) framework — including hardware PLP, firmware PLP, and PLN — provides flexible data protection.
Enterprise eTLC SSDs are designed to deliver stable performance for AI workloads, offering endurance options of 1 and 3 DWPD over a five-year period for varying workload intensities. Under sustained workloads, they maintain more than 90% random IOPS consistency, minimizing performance fluctuations. Firmware optimized for high-density computing enables low latency operation, while capacitor-based PLP and immersion cooling support ensure reliable performance in demanding deployment environments.
With more than 18 years of in-house firmware development expertise, SSSTC understands diverse storage requirements across industries and provides flexible customization options, including configurable over-provisioning, lifespan and capacity optimization, performance and power tuning, and application-specific firmware development. SSSTC remains committed to helping customers build stable, efficient, and sustainable AI storage infrastructures.
About SSSTC
Founded in 2008, SSSTC became a subsidiary of Kioxia Corporation in 2020 and delivers high-quality SSDs through in-house firmware and NAND expertise. For more information, visit the SSSTC website.
Remark: PCIe is a registered trademark of PCI-SIG.
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Computex 2026: SSSTC Expands Immersion-Cooling SSD Portfolio to Address AI Data Center Thermal Challenges
TAIPEI, June 2, 2026 /PRNewswire/ -- Life science research is entering an AI era, but most discovery teams still cannot use frontier models at scale. Advanced AI models, molecular simulation tools, scientific databases, inference optimization and GPU infrastructure remain fragmented across separate systems. For many pharmaceutical companies, ingredient innovators, biotech teams, and research groups, this makes AI adoption slow, costly, and technically demanding.
NYB.AI, a Singapore Artificial Intelligence (AI) technology startup developing infrastructure for molecular discovery and life science research, aims to address this gap with Vecura, its agentic AI platform that connects scientific models, biological data, molecular analysis tools, and GPU accelerated computing into a unified discovery workflow.
Vecura 2.0 builds on the original Vecura 1.0 platform, which provided access to AI models and scientific tools for molecular discovery. With the new agentic layer, Vecura 2.0 moves beyond tool access toward workflow execution. It is designed to help research teams define scientific objectives, retrieve relevant context, activate suitable models, compare outputs, and generate structured decision support with less manual coordination.
From model access to agentic workflows
Vecura was built around a simple premise: the next barrier in AI for science is not access to more models. It is the ability to make those models work together in discovery settings. The original Vecura platform brought hundreds of AI models, scientific tools, biological data, and molecular analysis capabilities into connected workflows, helping research teams move across compound analysis, target exploration, formulation research, toxicity assessment, and translational R&D without relying on separate systems at every step.
Vecura 2.0 extends this foundation with an agentic AI layer. The upgraded platform is designed to reason across the workflow by understanding research objectives, retrieving relevant scientific context, selecting suitable models, coordinating execution, comparing outputs, and generating structured next step recommendations. This evolves Vecura from a workflow platform into a more intelligent discovery system that can assist scientists at scale, closer to how real research decisions are made.
This agentic approach allows scientists to focus on research direction rather than infrastructure management. It also supports NYB.AI's broader vision to democratize molecular discovery by making advanced AI models, scientific tools, and GPU intensive workflows more accessible to teams beyond large pharmaceutical organizations and specialized computational labs.
Scaling access through NVIDIA technologies
NYB.AI is strengthening Vecura's agentic architecture for scientific discovery using NVIDIA technologies. As a member of the NVIDIA Inception program for startups, NYB.AI received access to NVIDIA Hopper GPUs through NVIDIA Innovation Lab, along with engineering guidance to advance Vecura's ability to plan, execute, and coordinate complex research tasks. This support enables Vecura to move beyond isolated model execution toward connected workflows where scientific context, model selection, inference, comparison, and decision support operate as one system.
Vecura is powered by NVIDIA technologies spanning agentic orchestration, scientific modeling, data and retrieval, and production deployment - all running on NVIDIA accelerated computing.
NYB.AI is also developing a token based access model for Vecura 2.0. Through platform credits, biopharma companies, ingredient companies, and research teams can access AI powered discovery workflows such as compound screening, bioactivity prediction, and molecular docking. This model allows users to run compute intensive scientific tasks through NYB.AI's platform without needing to build or operate their own infrastructure.
What's next?
NYB.AI is bringing Vecura 2.0 to the NVIDIA Inception Startup Showcase at the Inception Pavilion during InnoVEX 2026 (June 2–5, 2026, Taipei Nangang Exhibition Center). The showcase will give NYB.AI an opportunity to validate Vecura 2.0 with enterprise leaders, investors, ecosystem partners, and international buyers, and strengthens its visibility within NVIDIA Inception ecosystem — demonstrating how agentic AI can move beyond model experimentation into usable research infrastructure for molecular discovery teams.
At InnoVEX 2026, NYB.AI will demonstrate how Vecura 2.0 can support molecular discovery and life science research across pharmaceuticals, nutraceuticals, cosmetics, food science, functional ingredients, and consumer health. The platform reflects NYB.AI's broader mission to make advanced AI discovery infrastructure more usable, scalable, and accessible across the life science ecosystem.
About NYB.AI
NYB.AI is an AI biotechnology company developing infrastructure for molecular discovery and life science research. Its flagship platform, Vecura, is an agentic AI platform that connects AI models, scientific tools, biological data, retrieval systems, accelerated computing, and autonomous workflows to help life science teams shorten discovery cycles and prioritize high-potential candidates.
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NYB.AI Launches Vecura 2.0, Bringing Agentic AI Workflows to Molecular Discovery, with NVIDIA
