At ISC 2026, xFusion showcased scalable enterprise AI computing models that bridge hardware from edge devices to data centers.
Enterprise technology buyers at the Hamburg exhibition sought practical production frameworks. Hardware selection processes often overlook physical operating limits, and relying on public APIs exposes proprietary commercial data.
xFusion engineers responded with a four-tier hardware portfolio. The deployment structure scales processing capacity sequentially: individual workstations, workgroup clusters, corporate office appliances, and facility-level supernodes.
Personal edge processing devices
Engineers and specialized staff need dedicated local resources for complex 3D rendering and architectural simulation tasks. They process vast datasets locally before committing workloads to centralized computing clusters.
xFusion provides the FusionXtation X3 8000 Gen2 edge computing node as the foundation layer. Companies deploy these workstations to staff who need local execution of models with 70 billion to 200 billion parameters.
Hardware configurations pair Intel Core Ultra processors with dual professional-grade graphics processing units. Memory configurations include error-correcting DDR5 RAM up to 256 gigabytes and internal storage reaching eight terabytes.
Production environments report 70 percent faster 8K rendering output and up to a 50 percent boost in general AI processing performance compared to previous hardware generations. IT administrators maintain remote access through integrated Baseboard Management Controllers. Four 40-gigabit-per-second Thunderbolt ports handle external data transfers.
Workgroup data containment appliances
Uncontrolled data flows create compliance risks for regulated institutions. External application marketplaces expose corporate networks to malicious code. Development teams must build custom software securely to protect corporate intellectual property.
xFusion designed the FusionXpark appliance to meet this team-level compliance requirement. The platform enables engineering units to maintain regulatory standards during initial application design. Medical imaging teams and financial modelers process highly sensitive commercial data entirely isolated from external APIs.
Teams combine two independent FusionXpark units to process 405-billion parameter models locally on native CUDA environments. The system runs NVIDIA DGX OS directly from the factory. Developers gain immediate access to required toolchains. Network administrators route overflow processing demands securely into DGX Cloud through native integrations.
Operations departments need predictable infrastructure for automated customer service routines and complex financial approvals. xFusion manufactures the TokenBox as a centralized corporate processing appliance. The unit supplies token generation capacity across entire companies from a single on-premises installation.
Individual TokenBox nodes hold enough capacity to run models with 1.6 trillion parameters. This deployment model avoids the capital expense of building dedicated server rooms.
Internal data-center-grade liquid cooling mechanisms keep noise levels to 35 decibels during active computations, allowing facility managers to place these units directly in normal office environments. Pre-installed software and skills bypass lengthy configuration periods, accelerating return on investment.
Data center computing engines
Scaling computing capabilities across multinational corporate networks requires advanced thermal infrastructure. The final deployment tier focuses entirely on liquid-cooled racks and supernodes.
High-density infrastructure packages manage 240 kilowatts per cabinet. Hardware designs translate raw electrical input directly into floating-point operations per second. Self-developed low-loss core components reduce single-module operational expenditures by 15 percent.
Centralized corporate clusters rely on dense rack-mounted hardware integrated within this supernode architecture. The FusionServer G6550 V8 inference server operates in this tier, housing up to ten dual-width graphics processing units.
The FusionPoD liquid cooling computing platform manages the thermal output of these racks, achieving a partial Power Usage Effectiveness of 1.06. Liquid cooling loops extract heat using graphene pads and diamond cold plates that reach conductivity ratings of 1200 watts per meter-kelvin.
Processing hardware stalls without constant data ingestion. The FusionOne DFS storage solution provides the underlying data architecture for these compute clusters. A three-node cluster operating 72 NVMe drives achieves sequential read bandwidths of 200 gigabytes per second. The arrays scale to manage exabytes of total capacity while achieving 94.1 percent storage utilization through erasure coding.
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