Enterprise Agentic AI Solution

Full-stack infrastructure and services for accelerating autonomous AI workloads anywhere.

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Agentic AI marks a new era of intelligence, where AI moves beyond answering questions to taking action. Autonomous agents can perceive, reason, and execute multi-step workflows with minimal human intervention.

Agentic AI workloads expose new infrastructure demands - from concurrent inference and large context windows to secure, on-premises data control. ASUS provides end-to-end AI infrastructure solutions to build, govern, and operate enterprise AI agents across any environment.

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Why ASUS Solution Stack Use Cases Find Your Server FAQs

Deploy, govern & scale agents with confidence

ASUS delivers everything you need to turn agentic AI into measurable business outcomes

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Enterprise-grade security & governance

Enforce centralized security, granular permission boundaries, and full auditability across your entire agentic ecosystem.

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Production-grade reliability & visibility

Ensure stable, mission-critical operations with end-to-end observability, intelligent routing, and automated failover.

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Optimized performance at any scale

Power demanding AI workloads with enterprise GPU infrastructure engineered for high-throughput inference and long-context processing.

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Seamless integration & flexibility

Connect agents effortlessly with enterprise data, existing workflows, and hybrid edge-to-cloud deployments.

Build Your enterprise AI agents with ASUS

ASUS infrastructure solutions provide the complete environment required to build, govern and operate enterprise AI agents

Where Agents Meet Your Business
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Finance
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Public Sector
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Healthcare
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Regulated Infra
ASUS AI HUB

A unified platform for Harness Engineering to build, deploy, and orchestrate AI agents with centralized governance, security, and model & data access control.

ASUS AI Software Stack

Provides rapid deployment of containerized environments and essential services for AI Hub, with continuous infrastructure monitoring to ensure stable and reliable operations.

ASUS Server & Infrastructure

End-to-end AI infrastructure with high-performance compute, storage, and networking — built to power Agentic AI at scale.

Agentic AI in Action

Discover how ASUS empowers enterprises to deploy high-impact AI agents across industries

Download the Full Use Case 〉
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From Factory Trips to One-Click Fabric Selection

Break the physical sampling bottleneck with AI-driven material intelligence and 3D simulation. By digitizing fabric selection and visual search, enterprises eliminate worldwide physical swatch shipping, cutting product development timelines from months down to days.

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Full-Stack Clinical AI Infrastructure

Address rising healthcare demand and staff shortages with secure, on-premise clinical decision support. ASUS Smart Healthcare integrates AI infrastructure and medical devices directly into hospital workflows, driving predictive care while ensuring zero patient data leaves the site.

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Turn Expert Judgment into Autonomous IT

Turn expert judgment and tribal knowledge into a 24/7 autonomous AI teammate for incident resolution. Dobby DeepAgent traces complex log data overnight to eliminate blind spots, reducing troubleshooting times from hours to minutes and significantly lowering operational handover costs.

Choose the Right GPU Server for Your AI Agents
From Workload Scale to GPU Spec
Size your infrastructure by model parameters and workload profile
STEP 1
Understand the enterprise demand and Define the Business Use Case
STEP 2
Define the Agent Workflow, requirement and model strategy
STEP 3
Define the Performance & Scale
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Application
Large-scale model training, fine-tuning, & massive-scale inference
High-throughput LLM serving, enterprise RAG, & multi-agent orchestration
Lightweight AI inference, computer vision, & entry-level LLM deployment
Model Size in Parameters (LLM/MoE)
70B - 405B
13B - 175B
Up to 7B
Workload Profile
Rack-Scale Heavy
Mainstream Enterprise
Flexible Inference
Deployment / Cooling
Liquid Cooling (DLC) / Rack-Scale
Air / Liquid Hybrid
Air Cooled Standard
Recommended GPU Spec
NVIDIA HGX™ Rubin / Blackwell (NVL8/NVL72)
NVIDIA H200 NVL / B200 NVL
NVIDIA RTX PRO 6000 / MGX™-based Servers
ASUS Solution
From Agent Role to ASUS Solution
Match the right ASUS server to each agent's function in your multi-agent workflow
LLM and knowledge agents

High-throughput LLM serving and enterprise RAG for agents that read, retrieve and answer across company knowledge.

ESC8000A-E13P
NVIDIA H200 NVL / B200 NVL, 8-GPU

Mainstream enterprise inference

  • Up to 8 dual-slot GPUs in 4U
  • Air or liquid hybrid cooling
  • Dual AMD EPYC processors
  • High-speed NVMe storage
Learn More 〉
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Multimodal and vision agents

Agents that see and read: document understanding, video analytics and computer vision at the edge or in the data center.

ESC8000A-E13X
NVIDIA RTX PRO 6000 Blackwell

Flexible inference

  • Up to 8 RTX PRO 6000 GPUs
  • Air-cooled standard
  • Ideal for vision and multimodal pipelines
  • Entry to mid-scale deployment
Learn More 〉
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Mixed enterprise workloads

One platform for inference, RAG and orchestration side by side, sized for growing multi-agent estates.

ESC8000-E12P
Intel Xeon 6, NVIDIA H200 NVL

Mainstream enterprise

  • Up to 8 GPUs with PCIe 5.0
  • Balanced compute, memory and I/O
  • Air or liquid hybrid cooling
  • Enterprise management and security
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Code and tool-execution agents

Agents that write code, call tools and run multi-step workflows, where concurrency and low latency matter most.

XA P2N-E2
NVIDIA HGX Blackwell NVL8

Rack-scale heavy

  • 8 NVIDIA Blackwell GPUs, NVLink
  • Liquid cooling (DLC) or rack-scale
  • Large context and concurrent inference
  • ConnectX SuperNIC networking
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Frontier reasoning models

Trillion-parameter model inference, ultra-long-context deep reasoning, high-throughput token generation as the agent brain (orchestrator / planner model).

XA NR1I-E12L / LR
NVIDIA HGX Rubin NVL8 with dual Intel Xeon 6776P

Next-generation flagship inference compute

  • XA NR1I-E12L (3U): air-cooled CPU sled, lower entry cost, 25.7 kW/tray
  • XA NR1I-E12LR (2U): fully liquid-cooled, max density, 23.9 kW/tray, 7% less power than E12L
  • 100% liquid-cooled GPU sled on both; CPU sled air-cooled (3U) or liquid-cooled (2U)
  • 4096 GB DDR5 memory, 8x OSFP (ConnectX-9) + BF4 DPU (2x400 GbE)
  • Fully cable-less, board-to-board design with 54V busbar power
  • 2.5" NVMe hot-swap storage (3U) or fixed 8x E1.S storage (2U)
Learn More 〉
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FAQs

Generative AI produces content in response to a prompt. Agentic AI goes further - it perceives its environment, plans a sequence of actions, executes them, and learns from the outcome, largely without step-by-step human instruction.

Agentic AI workloads tend to run continuously (not just on-demand), coordinate multiple models or agents at once, and need to keep sensitive data on-premises. That typically means more concurrent GPU capacity, higher-throughput networking, and infrastructure sized for 24/7 operation rather than bursty requests.

It depends on the workload, and CPU matters as much as GPU. For GPU: a single-department assistant or workflow agent can run on a 2U server with up to 4 GPUs; large-scale multi-agent orchestration or RAG at enterprise scale typically needs 4U/7U servers with up to & GPUs or HGX-based rack-scale systems. For CPU: every agent runs a continuous loop of planning, sandboxed code execution, and tool calls that's CPU-bound, not just GPU-bound - so per-core performance and memory bandwidth matter as much as core count. See the configuration guide below.

Agentic AI's autonomy is exactly why infrastructure matters. Agents that can execute code, call tools, or access sensitive systems need hardware-level sandbox isolation and on-premises data control - not just software-level guardrails. That's a server architecture decision, not just a software one.

Ready to Build Your AI Agent Infrastructure?

contact ASUS today to accelerate your enterprise's intelligent transformation!

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