Singapore’s 374 AI companies

Singapore is the one AI ecosystem we have gone through company by company rather than sampled. 374 live products, most of them founded in the last two years, most of them pre-seed, and a market mix that looks nothing like the Bay Area’s. If you want to know what an AI ecosystem looks like when it is not organised around foundation models, this is the closest thing to a complete picture we hold.

What we know, and what we do not

This is a deliberately complete sweep rather than a sample, so the counts mean something — but the depth is uneven and it is worth saying which columns are thin. Only 46 of the 374 have a growth signal, because that requires a history of checks we have not accumulated yet. Only 37 carry a user rating. Founding year and category are complete for all 374.

So read what follows as a map of what exists and what it is working on, not as a ranking of which companies are winning. We have not held these products long enough to say that, and pretending otherwise would be the easiest way to be wrong in print.

An applied ecosystem, not a foundational one

The market mix is the most interesting thing in this data. Globally, the catalog is led by Coding, Image, Design and Writing — tools for making things. Singapore is led by Data, Healthcare, Finance, Ecommerce and Automation — tools for running things.

Healthcare over-indexes four to one, Automation almost four to one, Data more than two to one. Meanwhile Coding — 6.6% of the global catalog and the largest market we track — does not reach Singapore’s top six at all.

That is a coherent strategy rather than a gap. Singapore is small, heavily regulated, and positioned as a gateway into markets that are also heavily regulated. Building a general coding assistant from there means competing head-on with companies that are next door to the model providers. Building compliance-grade healthcare or finance tooling for Southeast Asia means competing with almost nobody, in a market where local regulatory knowledge is the moat.

Who is building what

Examples from each of the six largest markets. These are not rankings — the opportunity scores across this cohort are driven largely by category, and with so few carrying a growth signal, ordering them head to head would invent a precision the data does not have.

A pre-seed ecosystem

292 of 374 are pre-seed — 78% of the ecosystem, against 4.5% of the live catalog as a whole. That single chart explains most of what is unusual here: this is not a mature cluster with a long tail of startups attached, it is mostly the long tail, and the shape of it will not be clear for another two or three years.

It also means the mortality data has not caught up. We recorded one shutdown among the Singapore cohort in the September sweep, which reads as an astonishingly low failure rate and is nothing of the kind — these companies are simply too young to have failed yet. Our mortality report shows that failure typically shows up eighteen to twenty-four months after launch.

What to take from it

If you are building in the region, the mix tells you where the crowd already is. Data, Healthcare and Finance are where Singapore’s founders have concentrated; they are also where the local advantage is real. The genuinely open positions are in the markets that barely appear here at all.

If you are investing, the stage distribution is the number to hold onto. Four in five of these companies have not raised a priced round. That is an enormous amount of unfiltered supply, and most of the usual signals — growth, retention, revenue quality — do not exist for them yet, ours included.

If you are comparing ecosystems, resist reading Singapore’s second place by volume in our hub table as a claim about the world. It is second because we counted it properly. What is genuinely comparable is the mix, and the mix is the finding.

Photo: Alesia Kozik / Pexels. Colour-graded for Falcoscan.

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