The AI Ecosystem Stack

About this Deep Dive: The AI Ecosystem Stack

The AI Ecosystem Stack maps the companies that make modern AI possible — from energy generation at the base of the stack to the applications people use at the top — and shows where the binding constraints sit at each level. This note explains how the map was built, what the fields mean, and where coverage is deliberately selective.

Snapshot as of June 1, 2026 — 521 companies, across 11 layers and 24 segments.

Structure: layers and segments

The stack's layers are adapted from Jensen Huang's five-layer view of AI infrastructure — energy, chips, compute infrastructure, models, and applications — in which every layer depends on the ones beneath it. We expanded that five-part frame into a more granular set of layers, so that distinct constraints (for example, power generation versus data-center physical infrastructure) appear as separate levels rather than collapsed together.

Within each layer, the segments were defined by Suhas Pai, Hudson Labs' CTO, to capture the meaningful sub-divisions of activity that companies actually compete in.

How companies were identified and classified

For each layer, Hudson Labs' Co-Analyst reasoning model surfaced the relevant companies, drawing on Hudson Labs market intelligence — company releases, earnings-call transcripts, and 10-K filings — together with web search. Each company was then classified into a segment within its layer.

Deep dive analysis

Every company was then run through a consistent loop:

• Positioning and moat — We established each company's position in the ecosystem and the basis of its moat from earnings and conference calls and web sources, and flagged any bottleneck tied to that moat. Moat descriptions reflect the company's current, demonstrated state — not future roadmap or promise.
• Segment bottlenecks — We identified the bottlenecks associated with each segment based on the disclosure from the companies within the segment, paired with web results.
• Criticality — The reasoning model weighed the critical bottlenecks within a company's segment against the company's own disclosures on its moat and operationalization, and from that assessed how critical the company is to the ecosystem.

Coverage and completeness

Most layers aim for comprehensive coverage of the companies that matter at that level.

The exception is the top of the stack. For the Applications, Applications & edge AI, Data & content, and Data & AI infrastructure software layers, the universe is too broad to enumerate in full. For these layers we do not attempt complete coverage; instead we include a representative sample of the key names. Counts and rankings within these layers should be read as illustrative of the most important players rather than exhaustive.