Unlock the Power of Generative AI in Your Private Cloud
Build and deploy secure, high-performance AI applications on-premises with VMware Cloud Foundation and NVIDIA AI Enterprise. Fine-tune large language models, deploy RAG workflows, and run inference workloads while maintaining complete control over your data, addressing privacy, compliance, cost, and performance requirements.
Enterprise AI Challenges
Data Privacy & Security
Sending sensitive corporate data to public cloud AI services creates compliance and intellectual property risks.
Regulatory Compliance
Meeting diverse legal requirements across industries and countries demands strict access control and audit readiness.
Infrastructure Complexity
Deploying and managing AI workloads requires specialized GPU infrastructure, networking, and orchestration expertise.
Cost Unpredictability
Token-based billing models in public clouds make AI costs difficult to forecast and control at enterprise scale.
Model Governance
Lack of controls for downloading, testing, and deploying large language models creates security and quality risks.
Performance at Scale
Running production AI inference workloads demands consistent, high-performance infrastructure with proper resource sharing.
Development Speed
Time-consuming infrastructure provisioning and complex deployment processes slow AI application development cycles.
Multi-Model Management
Supporting diverse AI models and frameworks across development, testing, and production environments adds operational burden.
Platform Architecture
VMware Cloud Foundation
Industry-leading private cloud platform providing secure, comprehensive infrastructure for AI workloads. Delivers enterprise-grade virtualization, software-defined storage with vSAN, software-defined networking with NSX, and unified lifecycle management through SDDC Manager for simplified operations.
NVIDIA AI Enterprise
Production-ready AI software platform with optimized frameworks, tools, and pretrained models. Includes NVIDIA NIM inference microservices, NeMo for model customization, Triton Inference Server, TensorRT for optimization, and support for 4,500+ open-source AI packages with CVE management and long-term support.
Private AI Package
VMware-developed capabilities for simplified AI deployment including Model Store for secure model governance with RBAC, Model Runtime for scalable inference, Vector Database for RAG workflows, Deep Learning VMs, Data Indexing and Retrieval Service, AI Agent Builder, and GPU monitoring dashboards.
NVIDIA GPU Integration
Native support for NVIDIA A100, H100, L40S, and other Tesla GPUs with vSphere Direct Path I/O, GPU virtualization via vGPU, multi-instance GPU (MIG) for workload isolation, and GPU time-slicing. Delivers consistent performance for training, fine-tuning, and inference at any scale.
Core Solution Capabilities
Secure Model Governance
Download, catalog, and manage foundation models from public registries or internal sources with built-in role-based access control. Model Store provides versioning, scanning, and approval workflows ensuring only validated models reach production, with complete audit trails for compliance and governance.
Accelerated Inference
Deploy models as production-ready microservices using NVIDIA NIM with automatic optimization and scaling. Model Runtime handles resource scheduling, GPU allocation, and load balancing across multiple instances, delivering high throughput and low latency for real-time AI applications.
Enterprise RAG Workflows
Build retrieval-augmented generation applications with integrated vector database, document indexing, and semantic search capabilities. Connect your proprietary data sources, create embeddings, and enable LLMs to provide accurate, context-aware responses grounded in your enterprise knowledge.
Model Customization
Fine-tune foundation models on your proprietary data using NVIDIA NeMo framework with parameter-efficient techniques. Adapt models to domain-specific terminology, industry knowledge, and use cases while maintaining data sovereignty and reducing computational requirements compared to training from scratch.
How It Addresses Enterprise Challenges
Business Outcomes
Maintain data sovereignty with complete control over sensitive information, models, and inference results in your private cloud.
Accelerate time-to-production with pre-validated infrastructure, turnkey deployment, and simplified operations from day one.
Reduce total cost of ownership by eliminating public cloud egress fees, API charges, and unpredictable token-based billing.
Meet compliance requirements for healthcare, financial services, government, and other regulated industries with audit-ready controls.
Enable enterprise-scale AI with GPU virtualization, multi-tenancy, and resource sharing across hundreds of concurrent users.
Protect intellectual property by keeping proprietary models, training data, and fine-tuning processes within your infrastructure.
AI Development & Operations Capabilities
Model fine-tuning and customization with NVIDIA NeMo framework supporting parameter-efficient methods like LoRA and P-Tuning.
Production inference serving via NVIDIA NIM microservices with automatic model optimization and horizontal scaling.
RAG implementation toolkit including vector database, document chunking, embedding generation, and semantic retrieval.
Pre-built development environments with Jupyter notebooks, PyTorch, TensorFlow, and popular AI frameworks ready to use.
GPU resource management with dynamic allocation, multi-instance GPU support, and fair-share scheduling across teams.
Comprehensive monitoring for GPU utilization, model performance, inference latency, and cost tracking with built-in dashboards.
Security and governance with model scanning, access controls, encryption at rest and in transit, and complete audit logging.
Multi-framework support for PyTorch, TensorFlow, JAX, ONNX, and other popular AI/ML frameworks on a unified platform.
Technical Components
VMware Infrastructure
- vSphere 8.0 with GPU pass-through and virtualization
- vSAN for high-performance AI storage
- NSX for software-defined networking and security
- Tanzu for Kubernetes-based AI workload orchestration
- Aria Operations for infrastructure monitoring
NVIDIA AI Platform
- NVIDIA NIM inference microservices
- NVIDIA NeMo for model customization
- Triton Inference Server for multi-framework serving
- TensorRT and TensorRT-LLM optimization
- CUDA, cuDNN, NCCL for GPU acceleration
Private AI Services
- Model Store with version control and RBAC
- Model Runtime for scalable inference
- Vector Database (Milvus-based)
- Data Indexing and Retrieval Service
- Pre-configured Deep Learning VMs
Enterprise Use Cases
Intelligent document processing – Extract, classify, and analyze contracts, invoices, and regulatory filings with domain-specific LLMs.
Customer service automation – Deploy conversational AI chatbots with access to internal knowledge bases and product documentation.
Code generation and analysis – Accelerate software development with AI assistants trained on internal codebases and best practices.
Fraud detection and risk analysis – Identify anomalies and suspicious patterns in financial transactions using fine-tuned models.
Medical image analysis – Analyze radiology images, pathology slides, and patient records while maintaining HIPAA compliance.
Supply chain optimization – Forecast demand, optimize inventory, and predict disruptions using proprietary operational data.
Simplify your Complexity
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