July 2026

The AI Infra Ecosystem

The AI Infra Ecosystem Map is a living reference of 293 companies building the infrastructure layer of AI, mapped across Jensen Huang's five-layer cake — Application, Models, Infrastructure, Chips, and Energy. The middle layer — Infrastructure — is cut open and expanded in full across seven sublayers: cloud & compute, inference, agents, orchestration, MLOps, storage & networking, and data centers.

293Companies
5Layers
66Open source
Leader
Major
Emerging
Startup
OSS Open source
Region
⌕
Methodology · how companies are chosen

This map expands the infrastructure layer of AI in full; the surrounding four layers (Application, Models, Chips, Energy) appear as context only. A company is listed when it ships a production product in one of the seven infrastructure sublayers with meaningful adoption, funding, or open-source traction. Tiers reflect market presence, not endorsement — Leader (category-defining), Major (established), Emerging (scaling), Startup (early-stage); OSS marks open-source-core projects. It is deliberately a living draft — additions and corrections are welcome.

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Frequently asked questions

What is the AI Infra Ecosystem Map?

The AI Infra Ecosystem Map is a living reference of 293 companies building the infrastructure layer of AI. It organizes the market across the five layers of the AI stack — Application, Models, Infrastructure, Chips, and Energy — and expands the Infrastructure layer in full across seven sublayers: AI Cloud & Compute, Inference & Model APIs, Agent Infrastructure, Cluster Orchestration & Tenant Isolation, MLOps & Training, Storage & Networking, and Data Center & Hardware.

What is the AI infrastructure layer?

The AI infrastructure layer sits between AI models and the chips they run on. It includes GPU clouds and compute providers, inference and model-serving platforms, agent infrastructure (sandboxes, memory, tool use), Kubernetes and cluster orchestration, MLOps and training tooling, high-performance storage and networking, and the data centers, power, and cooling that everything runs on.

How are companies selected for the map?

A company is listed when it ships a production product in one of the seven infrastructure sublayers with meaningful adoption, funding, or open-source traction. Tiers reflect market presence, not endorsement: Leader (category-defining), Major (established), Emerging (scaling), and Startup (early-stage). Open-source-core projects carry an OSS badge.

How many companies are on the map?

The July 2026 edition maps 293 companies, of which 66 are open-source-core projects. The map is a living draft and is updated as the market evolves; suggestions and corrections are welcome via the suggestion form.

What are the five layers of the AI stack?

The five-layer model of the AI stack, popularized by NVIDIA CEO Jensen Huang, consists of: (1) Application — AI products, developer tools, and agents; (2) Models — frontier and open-weight labs; (3) Infrastructure — cloud, inference, orchestration, MLOps, storage, and data centers; (4) Chips — GPUs, accelerators, and memory; and (5) Energy — power, cooling, and data-center capacity.

Full company index text version · 293 companies · 66 OSS

The AI Infra Ecosystem Map is a curated, living reference of 293 companies building AI infrastructure, organized across the five layers of the AI stack — Application, Models, Infrastructure, Chips, and Energy — with the Infrastructure layer expanded across seven sublayers. The complete list below mirrors the interactive map above in plain text.

Infrastructure — expanded in full

AI Cloud & Compute · Hyperscalers, GPU-native clouds, sovereign clouds, and GPU marketplaces 84 companies

Hyperscalers

GPU-Native AI Clouds

GPU Marketplaces

Sovereign & Regional

Inference & Model APIs · Managed inference providers, serverless model APIs, and inference-as-a-service platforms 12 companies

Inference API Providers

Agent Infrastructure · Sandboxes, durable execution, memory, and tool infrastructure for running autonomous agents in production 22 companies

Sandboxes & Code Execution

Durable Execution & Orchestration

Memory & State

Tools, Browsers & Protocols

Cluster Orchestration & Tenant Isolation · Kubernetes platforms, tenant cluster orchestration, GPU scheduling, AI factory software 42 companies

Kubernetes Platforms

GitOps & Delivery

Tenant Cluster Orchestration

AI Factory Platforms

GPU Scheduling

Security, Policy & Identity

Workload Orchestration

MLOps & Training · Experiment tracking, distributed training, inference engines and observability tooling 27 companies

Training & Experiment Tracking

Inference Engines & Serving Frameworks

Observability & Evaluation

Storage & Networking · Parallel storage, object storage, vector databases, high-speed interconnects 31 companies

AI-Optimized Storage

Vector & Analytical Databases

Network Silicon & Switches

Network Automation & Multi-Tenancy

Optical & Emerging Interconnect

Data Center & Bare Metal · Colocation operators, cooling, power, server OEMs, bare metal provisioning 24 companies

Colocation & DC Operators

Cooling & Power

Server OEMs

Bare Metal Provisioning

Context layers

Applications · AI products, developer tools, vertical software, agent frameworks 25 companies

AI-Native Developer Tools

Agent & LLM Frameworks

Vertical AI

Analyst, Media & Events

Models · Foundation models, open-weight releases, model hubs 11 companies

Frontier Model Labs

Model Hubs & Local Inference

Chips · GPUs, custom ASICs, HBM memory, server systems 19 companies

GPU & Accelerators

HBM & Memory

Server Systems

Energy · Power, cooling, data centers, bare metal provisioning 10 companies

Data Center Operators

Cooling & Power

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