Modern AI environments must support diverse workloads, from vision and language to agentic and retrieval workflows. Co-developed blueprints combining enterprise servers, GPU acceleration, and AI software reduce deployment risk and accelerate production across edge and data center environments. Read this overview to learn more.
Modern AI environments have outgrown single-purpose infrastructure. Deployments must support vision, language, reasoning, retrieval, and agentic workflows, each with unique performance profiles. Without workload-specific architectures, organizations risk delays and inefficiencies.
This overview outlines a blueprint-based approach to simplify multi-workload AI infrastructure and accelerate production. Highlights include:
Validated blueprints for edge, data center, and distributed environments
GPU-accelerated platforms with enterprise AI software
Blueprints for video analytics, healthcare, retail, robotics, and fraud detection
Explore the full framework in the product overview.
