AI Factory in a Box
AgilityFlexAI B300 HGX POD
Production-ready AI infrastructure — integrated as one system
AgilityFlexAI combines NVIDIA HGX B300 compute, high-speed networking, DDC hybrid-cooled cabinets, IBM Storage Scale System 6000, and NVIDIA enterprise software in a pre-engineered platform designed to reduce deployment complexity.
Compute, fabric, cooling, storage, and software are engineered as one stack before the system reaches the data center so B300-class performance is not constrained by the infrastructure around it.
Request a Consultation
144
PFLOPS FP4 Tensor Core performance per 8-GPU HGX B300
2.3 TB
HBM3e GPU memory per HGX B300 node
800G
Scale-out network connectivity per GPU with ConnectX-8
330
GB/s-class sequential storage bandwidth
Key Advantages
Designed to Remove Integration Guesswork
The pod approach treats every major subsystem as part of one validated AI platform.
Done Right the First Time
ADS integrates and validates the complete platform before delivery, reducing deployment risk and tuning cycles.
No Bottlenecks by Design
Compute, storage, cooling, and network fabrics are sized together so one subsystem does not starve another.
Single Point of Accountability
One partner coordinates the integrated solution and support path across the core components.
Independent Scalability
Compute and storage can expand along different curves as models, data sets, and user demand change.
Best-of-Breed Integration
NVIDIA, IBM, and DDC technologies are combined around a coherent system architecture.
Lower Facility Burden
Hybrid cooling supports very high rack densities while reducing reliance on traditional room-level air cooling.
Technical Highlights
A Complete Infrastucture for Blackwell Ultra AI
Every subsystem is selected to sustain the memory bandwidth, network traffic, storage I/O, and thermal load of dense Blackwell Ultra training, reasoning, inference, and HPC environments.
GPU Compute
NVIDIA HGX B300 Blackwell Ultra
✓
8 NVIDIA B300 SXM GPUs per HGX node
✓
288 GB HBM3e per GPU — up to 2.3 TB per node
✓
Fifth-generation NVLink with 14.4 TB/s aggregate GPU interconnect bandwidth
✓
Up to 144 PFLOPS FP4 Tensor Core performance
Network Fabric
800G Scale-Out GPU Networking
✓
Integrated NVIDIA ConnectX-8 SuperNICs with 1:1 GPU-to-NIC topology
✓
Up to 800 Gb/s connectivity per GPU for east-west traffic
✓
NVIDIA Spectrum-X Ethernet or Quantum-X800 InfiniBand
✓
Leaf-spine / Clos fabrics for distributed training and inference
Cooling
DDC Hybrid-Cooled Cabinets
✓
52U sealed cabinet architecture
✓
Up to 200 kW-class cabinet support
✓
Hybrid / liquid-ready thermal management
✓
Designed for sustained B300-class power and thermal density
Software
NVIDIA Enterprise AI Software
✓
NVIDIA AI Enterprise software stack
✓
NVIDIA Mission Control for AI data center operations
✓
Run:ai technology for multi-tenant GPU scheduling and utilization
✓
Integrated monitoring, lifecycle management, and production workflows
Storage
IBM Storage Scale System 6000
✓
High-throughput parallel flash storage
✓
GPUDirect Storage integration
✓
Multi-protocol access across file and object interfaces
✓
Designed to sustain large checkpoint and training data flows
Delivery
Integrated Deployment & Support
✓
Factory integration and validation
✓
Day-one production readiness objective
✓
Single-vendor coordination for the delivered stack
✓
Architecture designed for future expansion
AI Infrastructure
Where the B300 POD Fits
The architecture is aimed at organizations that need dense accelerated compute without taking on a multi-vendor integration project.
Large Model Training
Sustained distributed training across dense GPU nodes with high-speed east-west fabric.
High-Volume Inference
Scale-out inference for generative AI, recommendation, vision, and other accelerator-heavy services.
Research AI
Shared AI infrastructure for labs, universities, and engineering organizations with evolving model requirements.
Accelerated HPC
GPU-enabled simulation, scientific computing, and hybrid AI/HPC workflows.
Model Checkpointing
Parallel storage and high network bandwidth for frequent large checkpoint operations.
Multi-Team GPU Operations
Enterprise scheduling and orchestration for shared GPU capacity across teams and projects.
Stand Up an AI Factory
Want to Review the B300 POD Architecture?
ADS can map the pod to your model profile, facility constraints, storage requirements, and deployment timeline.
Request a Consultation
Applied Data Systems
©2026 Applied Data Systems