
Accelerate AI Analytics Workloads
High-performance, low-cost data storage and retrieval platform for AI analytics. Solves slow AI training data loading and weak correlation between structured data and raw video.
AI video analytics projects require rapid access to massive historical video datasets for model training and inference. Traditional storage cannot provide the IOPS and bandwidth needed, creating data loading bottlenecks that slow AI development cycles.
Build a tiered data lake architecture with NVMe SSD cache for hot training data, high-density HDD for warm data, and object storage for cold archives. Implement a metadata catalog that links structured AI outputs back to raw video segments for efficient retrieval.
NVMe SSD hot tier delivers 10× faster training data loading vs. traditional storage.
Metadata catalog links AI output (labels, detections) back to raw video segments in milliseconds.
GPUDirect interface eliminates CPU bottleneck for maximum AI throughput.
End-to-end pipeline from ingestion to annotation, training, and model deployment.
Automatic hot/warm/cold tiering reduces AI infrastructure cost by up to 50%.
Native integration with PyTorch, TensorFlow, NVIDIA Triton, and major AI frameworks.
Our solution architects are ready to design a customized deployment plan for your specific requirements.