Between August 2025 and July 2026, vertical AI companies raised $3.07 billion across 73 disclosed deals covering 72 companies. Legal, insurance, construction, and healthcare accounted for 72.64% of that disclosed capital.
Within those categories the results have been extraordinary. Legora reached $100 million in annual recurring revenue in eighteen months, which Bessemer described as the fastest growth trajectory in enterprise software history. Harvey closed the second quarter of 2026 at around $300 million ARR and an $11 billion valuation.
The reasonable inference from those numbers is that legal AI is a good business. The unreasonable inference, which is nonetheless the common one, is that legal AI is therefore a good place for you to start.
Step 1
Name the vertical you are considering as narrowly as you can
Step 2
Search for AI funding announcements in it from the last twelve months
Step 3
If the results are large, expect to be outspent rather than outbuilt
Step 4
If the results are empty, confirm the industry has budget and a real problem
Step 5
Move on the second case, where your domain knowledge is scarce rather than standard
What concentration actually indicates
A funding map shows where capital has decided to compete. It does not show where value is unclaimed. Those two things are close to opposites for anyone building without funding.
In a vertical with $2 billion of deployed capital behind it, your competition includes companies who can afford to lose money acquiring customers for three years, employ people whose entire job is one part of the problem, and buy the data access you would have to negotiate for. None of that makes them better at the work. It makes them impossible to outspend, and most competitive situations in a well-funded category get resolved by spending.
The bar has moved with the money. Getting from seed to Series A now takes eighteen to twenty-four months and generally requires $1.5 million to $3 million in ARR with net revenue retention above 110%. That is the standard in funded categories, and it is the pace you would be measured against by anyone comparing you to the alternatives.
“A funding map shows where capital has decided to compete. It does not show where value is unclaimed. For anyone building without funding, those are close to opposites.”
The other 27%
Roughly a quarter of the disclosed capital went everywhere else, spread across a long list of industries with no concentration in any of them.
A funding map shows where capital has decided to compete.
Those are the categories where a single competent operator can still be the best available option. Not because the problems are smaller, but because nobody has decided they are a category yet, which means no one is being funded to take them from you.
Turn what you know into what you own.
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Join the WaitlistThe test for whether an industry is in this group is unromantic. If a search for AI companies serving it returns a funding announcement in the last year, it is being contested. If it returns nothing but trade press and a few directories, you are early in a way that money has not yet noticed.
Why an unfunded builder should want this
Being early in an ignored industry means slower growth and far better odds. The customers exist, they are not being courted, and the price they will pay is set by what the problem costs them rather than by what a funded competitor is discounting to.
It also means the moat is the thing you already have. In a crowded vertical, domain knowledge is table stakes because every competitor hired someone who has it. In an ignored one, domain knowledge is scarce, because the reason nobody has built there is usually that nobody who understood the industry also knew a product was possible.
How to use the funding data properly
Read it as a competition map, not an opportunity map. Search for recent funding in the vertical you are considering. If the answer is a large number, you have learned something useful and mildly discouraging. If the answer is nothing, check that the industry has money and a problem, and then move.
The four crowded verticals will produce several very large companies over the next few years. Almost none of them will be founded by someone reading this, and that is a reason to look elsewhere rather than a reason for disappointment.
See how to find a vertical in an ignored industry for the search itself, twelve vertical SaaS industries for 2026 for candidates, and boring vertical tools beating AI wrappers for what wins in these markets. How the system works covers structuring the search.