29 US AI Companies and Where They're Actually Headquartered

29 US AI Companies and Where They're Actually Headquartered

A few years ago, "AI company" basically meant San Francisco.

That is no longer true, and the way it stopped being true is more interesting than the fact itself. Other cities did not become smaller versions of the Bay Area. They each took a layer.

The Map

San Francisco. OpenAI, Anthropic, Databricks, Scale AI, Perplexity, Midjourney, Cursor, Harvey, Sierra, Decagon.

Silicon Valley. NVIDIA, xAI, Glean, Groq, Cerebras, Figure.

New York. Runway, Clay, Hugging Face, Hebbia.

Boston. Liquid AI, Suno, DataRobot.

Everywhere else. Ai2 in Seattle. Crusoe in Denver. Jasper in Austin. Abridge in Pittsburgh. CoreWeave in New Jersey. Anduril in Southern California.

Sixteen of the twenty-nine sit within a few miles of each other in the Bay Area. The concentration is still real and it would be silly to argue otherwise.

The Real Story Is The Other Thirteen

What changed is that the companies outside the Bay Area are not overflow. They are specialists located next to the industry they sell into.

Boston is becoming a foundation-model hub. Liquid AI is the clearest example of a serious model play outside California, and it exists because of MIT rather than in spite of the geography.

Pittsburgh quietly turned into the home of medical AI. Abridge is there for the same reason Carnegie Mellon and UPMC are there. Clinical AI needs clinical partners, and those are not in SoMa.

New York owns the creative and go-to-market layer. Runway next to advertising and media. Clay next to the sales organisations that buy it. Hebbia next to the finance firms it serves.

Denver and New Jersey own compute logistics. Crusoe and CoreWeave are infrastructure businesses whose constraint is power and land, not engineering talent density.

The pattern: the model layer clusters around research capital, and everything above it clusters around customers.

How To Read This As A Supply Chain

If you are building a go-to-market motion in 2026, this map is not industry trivia. Every company on it is a building block you can wire into how you find, reach, and close customers.

Some of them you will use directly. Clay for data orchestration. Hugging Face if you are running anything open-source. Some of them you will use through other products without knowing it.

The question worth asking about your own stack is which block does what, and whether you actually need a separate block for each job. Most teams accumulate tools by layer without ever mapping which layer each one occupies, which is how you end up paying three vendors for overlapping enrichment.

Why Proximity Still Matters In A Remote World

It is fair to ask whether headquarters means anything when the engineers are distributed anyway.

It means less than it did for hiring and more than it did for selling. The reason Rogo is in New York and Abridge is in Pittsburgh is not where the developers sit. It is that a product for investment bankers gets built faster when you can have coffee with investment bankers, and a clinical product needs a hospital that will let you watch the workflow.

That is the durable advantage in applied AI. Not talent access, customer access.

What This Predicts

If the pattern holds, expect the next wave of valuable AI companies to appear in cities nobody currently associates with tech, clustered around whatever industry dominates locally.

Insurance AI in Hartford. Logistics AI in Memphis. Energy AI in Houston. Not because those cities will develop startup ecosystems, but because the domain knowledge and the buyers are already there, and that turned out to matter more than proximity to a model lab.

The teams that win will not be the ones with the most tools. They will be the ones who know which block does what.

The Clusters And What They Own

Frequently Asked Questions

Is San Francisco still dominant in AI?

On count, clearly. Sixteen of these twenty-nine companies sit within a few miles of each other in the Bay Area. What changed is that companies outside it are no longer overflow, they are specialists located next to the industry they sell into.

Why is medical AI concentrated in Pittsburgh?

Carnegie Mellon supplies the research base and UPMC supplies the clinical partner. Clinical AI needs a hospital willing to let you watch the workflow, and that access matters more than proximity to a model lab.

Does headquarters location still matter if teams are remote?

Less for hiring, more for selling. The reason applied AI companies cluster near their buyers is customer access, not talent access. You can hire an engineer anywhere. You cannot easily get repeated informal time with investment bankers or clinicians from another city.

What does this predict about the next wave?

If the pattern holds, valuable AI companies will keep appearing in cities with a dominant local industry rather than a startup ecosystem: insurance in Hartford, logistics in Memphis, energy in Houston. The domain knowledge and the buyers are already there.

How should a GTM team use this map?

As a supply chain rather than as news. Every company on it is a component you can wire into how you find, reach, and close customers. Map which layer each of your current tools occupies, and you will usually find three vendors covering one job and nobody covering another.

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Headquarters locations reflect publicly reported data as of mid-2026.