Skip to main content
Cloud / AWS / Products / AWS AI Factories - AI Infrastructure in Your DC

AWS AI Factories - AI Infrastructure in Your DC

AWS AI Factories: dedicated AWS AI infrastructure with Trainium and NVIDIA GPUs deployed in your own data center, run like a private AWS Region.

Machine Learning
Pricing Model Custom / contact AWS account team (no public pricing)
Availability Deployed in the customer data center, incl. EU
Data Sovereignty Data residency in your own data center, EU suitable
Reliability N/A SLA

What is AWS AI Factories?

AWS AI Factories is dedicated, high-performance AWS AI infrastructure that AWS builds and operates directly inside the customer’s data center. Instead of running AI workloads in a public cloud region, the customer provides space, power and network connectivity, while AWS handles deployment, optimization and operation of the hardware and services. The environment operates much like a private AWS Region and is built exclusively for one customer or a designated trusted community.

AWS AI Factories solves the problem of building large AI capacity without violating strict data residency and sovereignty requirements. Building comparable AI infrastructure independently is slow and complex in procurement, setup and optimization. AWS AI Factories instead delivers a pre-integrated full stack of AWS Trainium, the latest NVIDIA GPUs, plus specialized networking and storage, and according to AWS accelerates the AI buildout by months or years compared with building independently.

Core Features

  • Dedicated infrastructure in your own DC: AWS builds and operates a physically isolated, full-stack AI infrastructure inside the customer’s data center, which provides space, power and network connectivity. The environment runs like a private AWS Region.
  • Hardware stack of Trainium and NVIDIA GPUs: A combination of AWS Trainium accelerators (including Trainium3-class Trn UltraServers) and the latest NVIDIA GPUs (for example Blackwell GB300 NVL72), complemented by specialized low-latency networking and high-performance storage.
  • Integrated AWS AI and ML services: Core services such as Amazon Bedrock and Amazon SageMaker AI, plus database and security services, provide capability parity with public AWS Regions.
  • Sovereignty and isolation: A fully separated environment operated exclusively for one customer or a trusted community, designed to support workloads across different classification levels.

Common Use Cases

AI workloads with strict data residency requirements: Governments and regulated industries run training and inference inside their own data center, so sensitive data does not leave the site and sovereignty requirements are met.

Fast buildout of large AI capacity: Organizations that need significant AI compute quickly receive a pre-integrated full stack instead of handling procurement, setup and optimization themselves.

Dedicated AI zones for trusted communities: An exclusively operated, physically isolated environment serves as a shared AI platform for one customer or a designated trusted group, with clear separation and independent operation.

Benefits

  • Data and AI workloads stay inside your own data center, supporting data residency and sovereignty.
  • A pre-integrated full stack of Trainium and NVIDIA GPUs significantly shortens the AI buildout compared with building independently.
  • Capability parity with public AWS Regions through integrated services such as Amazon Bedrock and Amazon SageMaker AI.

Integration with innFactory

As an AWS Reseller, innFactory supports you with the adoption and operation of this service.

Typical Use Cases

AI workloads with strict data residency and sovereignty requirements
Training and inference for governments and regulated industries
Building a dedicated, physically isolated AI environment in your own DC
Fast AI buildout instead of building the infrastructure yourself

Frequently Asked Questions

What is AWS AI Factories?

AWS AI Factories is dedicated, rapidly deployable AWS AI infrastructure that AWS builds and operates inside the customer's own data center. The customer provides space, power and network connectivity, while AWS handles deployment and management. The environment operates much like a private AWS Region and combines AWS Trainium and NVIDIA GPUs with networking, storage and AWS AI services such as Amazon Bedrock and Amazon SageMaker AI.

When should I use AWS AI Factories?

AWS AI Factories is a good fit when AI workloads must not leave your own data center for regulatory or sovereignty reasons. Typical scenarios are governments and regulated industries with strict data residency requirements, dedicated and physically isolated environments, and the fast buildout of large AI capacity without building the hardware yourself. The solution is designed to support workloads across different classification levels.

How much does AWS AI Factories cost?

There is no public price list for AWS AI Factories. It is deployed under a custom engagement with the AWS account team, depending on scope, hardware stack and operating model. In addition, the customer bears the costs for data center space, power and network connectivity. Clarify binding terms with AWS or your reseller.

How does AWS AI Factories support data sovereignty in the EU?

The infrastructure is deployed physically inside the customer's data center and provides a dedicated, isolated environment, so data does not leave your own site. AWS positions AWS AI Factories as part of its sovereignty options alongside the European Sovereign Cloud, Dedicated Local Zones and Outposts. For EU customers with strict data residency requirements, deployment in your own DC is a key advantage.

AWS Cloud Expertise

innFactory is an AWS Reseller with certified cloud architects. We provide consulting, implementation, and managed services for AWS.

Similar Products from Other Clouds

Other cloud providers offer comparable services in this category. As a multi-cloud partner, we help you choose the right solution.

Google Cloud

Agent Development Kit (ADK) - Multi-Agent Framework

Agent Development Kit (ADK): Google's open-source framework to build, evaluate, and deploy single- and multi-agent …

Pricing Free / open source (Apache 2.0); …
SLA N/A (framework); SLA depends on the chosen deployment target
Compare →
Azure

Foundry IQ - Knowledge Layer

Foundry IQ is the knowledge and retrieval layer for Microsoft Foundry: agents query unified knowledge bases through a …

Pricing Pay-as-you-go (free tier + free token …
SLA N/A (some features in preview, without SLA)
Compare →
Azure

Foundry Local - On-Device Local AI Runtime

Foundry Local: cross-platform AI runtime that runs models on-device via ONNX Runtime. OpenAI-compatible API, no cloud, …

Pricing Free, no per-token cost
SLA N/A (local execution, no service SLA)
Compare →
Google Cloud

Gemini on Vertex AI: Foundation Models via API

Gemini on Vertex AI: Google's foundation models (Gemini 3, 2.5 Pro, Flash) with long context and multimodality via one …

Pricing Pay-per-use (tokens), plus batch, …
SLA 99.9%
Compare →
Google Cloud

GKE Inference Gateway - LLM Routing on Kubernetes

GKE Inference Gateway: Kubernetes-native gateway for serving generative AI on GKE with LLM-aware routing and …

Pricing No separate product charge, you pay for …
SLA N/A (no dedicated SLA, the GKE SLA applies to the cluster)
Compare →
Azure

Microsoft Discovery - Agentic AI for R&D

Microsoft Discovery is an agentic AI platform on Azure that combines research agents, knowledge graphs, and HPC to …

Pricing Pay-per-use (Azure consumption + User …
SLA N/A
Compare →

68 comparable products found across other clouds.

Ready to start with AWS AI Factories - AI Infrastructure in Your DC?

Our certified AWS experts help you with architecture, integration, and optimization.

Schedule Consultation