New York’s artificial intelligence startup scene has changed dramatically in just a few years. What was once viewed as a smaller alternative to Silicon Valley has grown into one of the most important AI ecosystems in the United States, with billion-dollar startups operating across cybersecurity, finance, healthcare, accounting, legal technology, sales, real estate, video generation, and AI infrastructure.
The question is no longer whether New York can produce meaningful AI companies. The more useful question is which New York AI startups are becoming the biggest, which ones are growing the fastest, and what their rise tells us about the type of AI economy developing across the city.
Answering that question is harder than it first appears because private startups do not publish data in the same way that public companies do. Revenue is often private, employee numbers can change quickly, valuations may be several years old, and fundraising announcements do not always show whether a company is actually building a strong business.
That is why NYC Tech Journal created its own dataset instead of relying on a simple list of companies that recently appeared in the news.
For this analysis, we examined 15 major private AI companies that are headquartered in New York or are consistently identified by reliable public sources as New York-based. We reviewed public information on company valuations, disclosed funding, financing dates, business focus, founding dates, and available operating metrics through August 28, 2026.
We then created an original NYC AI Momentum Index that combines company scale with publicly visible funding momentum. The goal is not to pretend that private-company data is perfect. Instead, the index provides a consistent framework that helps compare companies using the information that is actually available.
The resulting picture is clear. New York is not producing one type of AI startup. It is developing several powerful groups at the same time.
Some companies, including Modal and Hugging Face, are building infrastructure used by other AI developers. Cyera is becoming a major force in data and AI security. Runway and General Intuition are pushing into advanced AI research. Meanwhile, companies such as AlphaSense, Basis, Norm AI, Rogo, Tennr, EliseAI, and Hebbia are applying artificial intelligence directly to expensive industries where New York already has deep expertise.
That mix is one of the strongest reasons New York’s AI ecosystem deserves serious attention.
The Biggest AI Startups in NYC at a Glance
Ranking private AI startups requires careful rules because not every valuation reported in the media represents the same type of transaction.
For the core dataset, we generally use the latest publicly disclosed valuation connected to a completed primary financing round. We do not automatically replace those values with reported acquisition discussions, proposed financing rounds, or employee secondary transactions.
This distinction prevents speculative numbers from making companies appear larger than they have actually been valued in completed primary financing.
Clay is a good example. The company completed an employee tender offer in January 2026 at a $5 billion valuation, but its previous primary financing valued it at $3.1 billion. General Intuition has reportedly discussed another round that could value the company at around $6 billion before new investment, but its most recent completed financing valued it at $2.3 billion. EliseAI has also been reported to be discussing a new round near $3.7 billion, while Hugging Face has reportedly attracted acquisition interest at a value well above its last funding-round valuation.
Those figures are useful because they show market interest, but they are not treated as completed primary valuations in our central ranking.
NYC Tech Journal’s 15-Company AI Dataset
| Company | Latest valuation used | Disclosed capital raised | Core market | Latest major financing |
|---|---|---|---|---|
| Cyera | $12.0B | ~$2.3B | Data security and AI security | $600M, 2026 |
| AlphaSense | $7.5B | ~$1.75B | Market intelligence | $350M, 2026 |
| Runway | $5.3B | ~$860M | Generative video and world models | $315M, 2026 |
| Modal | $4.65B | ~$466M | AI cloud infrastructure | $355M, 2026 |
| Hugging Face | $4.5B | ~$399M | Open-source AI platform | $235M, 2023 |
| Clay | $3.1B primary round | ~$204M primary funding | Sales and GTM automation | $100M, 2025 |
| General Intuition | $2.3B | ~$454M | Physical AI and world models | $320M, 2026 |
| EliseAI | $2.2B | ~$422M | Housing and healthcare automation | $250M, 2025 |
| Norm AI | $1.2B | $260M+ | Legal and compliance AI | $120M, 2026 |
| Basis | $1.15B | ~$138M | Accounting AI | $100M, 2026 |
| Rogo | $750M | $165M+ | Financial AI | $75M, 2026 |
| Hebbia | $700M | ~$161M | AI research and financial analysis | $130M priced round, 2024 |
| Tennr | $605M | ~$160M | Healthcare workflow AI | $101M, 2025 |
| Mirage | $500M | $175M+ | AI video creation | $75M growth financing, 2026 |
| Valence | ~$265M | ~$80M | Enterprise AI coaching | $50M, 2025 |
The table shows how quickly the upper end of New York’s AI market has expanded. Several startups that would have been considered major success stories at a $500 million valuation only a few years ago now sit well below the city’s largest private AI businesses.
Cyera alone is valued at $12 billion based on its latest completed financing. AlphaSense follows at $7.5 billion, while Runway, Modal, and Hugging Face form another group in the $4.5 billion to $5.3 billion range.
The next group includes Clay, General Intuition, and EliseAI, all of which have either crossed or moved close to multi-billion-dollar valuations. Behind them, Norm AI and Basis have already joined the unicorn club, while Rogo, Hebbia, Tennr, and Mirage remain within striking distance.
Chart: The Largest NYC AI Startups by Known Valuation
The simplest way to understand the size of the market is to compare the latest usable private valuations in our dataset.
| Rank | Company | Latest valuation used |
|---|---|---|
| 1 | Cyera | $12.0B |
| 2 | AlphaSense | $7.5B |
| 3 | Runway | $5.3B |
| 4 | Modal | $4.65B |
| 5 | Hugging Face | $4.5B |
| 6 | Clay | $3.1B |
| 7 | General Intuition | $2.3B |
| 8 | EliseAI | $2.2B |
| 9 | Norm AI | $1.2B |
| 10 | Basis | $1.15B |
| 11 | Rogo | $750M |
| 12 | Hebbia | $700M |
| 13 | Tennr | $605M |
| 14 | Mirage | $500M |
| 15 | Valence | ~$265M |
The gap at the top is significant, but it should not be interpreted as proof that the largest companies are necessarily growing the fastest.
Valuation measures investor expectations at a specific moment. It does not tell us how quickly a company reached that point, how recently the funding happened, how much revenue the company generates, or how efficiently it uses capital.
That is why we created a second layer of analysis.
Original Research: What Our NYC AI Dataset Shows
Across the 15 companies in our dataset, the combined latest known private-company valuation is approximately $46.72 billion. Those companies have raised roughly $7.99 billion in disclosed capital.
The median company in the group is valued at about $2.2 billion, while median disclosed funding is approximately $260 million.
Those figures show how mature the upper tier of New York’s AI market has become. A city once described mainly as a strong home for fintech and enterprise software now has several private AI companies valued at multiple billions of dollars.
The distribution, however, is far from even.
The Top Five Companies Control Nearly 73% of Known Valuation
Cyera, AlphaSense, Runway, Modal, and Hugging Face together account for approximately 72.7% of the known valuation across the 15-company sample.
Their share of disclosed funding is almost identical at roughly 72.9%.
This means New York’s AI market already has a clear power-law structure. Many promising companies are growing across the city, but a relatively small group captures most of the capital and valuation at the top.
That does not mean the smaller companies have less potential. It simply means the ecosystem has already produced a group of businesses operating at a much larger scale.
In some ways, the companies below that top group may be more interesting to watch because they still have room to move quickly. Norm AI, Basis, Rogo, Tennr, and Mirage are examples of companies that could change position significantly after another major funding round or a period of rapid customer growth.
Ten of the 15 Companies Are Already Unicorns
Using our conservative valuation rules, 10 of the 15 companies in the dataset are worth at least $1 billion.
Those companies are Cyera, AlphaSense, Runway, Modal, Hugging Face, Clay, General Intuition, EliseAI, Norm AI, and Basis.
Several others are not far behind.
Rogo reached approximately $750 million after its January 2026 financing. Hebbia’s last widely reported valuation was around $700 million, Tennr reached approximately $605 million, and Mirage’s last disclosed priced valuation was around $500 million.
This matters because the next generation of New York AI unicorns may already be visible.
New York Is Becoming a Vertical AI City
One of the strongest findings in our research is that New York’s AI economy is heavily tilted toward specialized business applications.
We divided the 15 companies into three broad categories: AI infrastructure and security, vertical enterprise AI, and creative or frontier AI.
| NYC AI category | Companies in dataset | Combined known valuation | Share of dataset valuation |
|---|---|---|---|
| AI infrastructure and security | 3 | ~$21.15B | 45.3% |
| Vertical enterprise AI | 9 | ~$17.47B | 37.4% |
| Creative and frontier AI | 3 | ~$8.10B | 17.3% |
Vertical enterprise AI represents nine of the 15 companies, which means it accounts for 60% of our sample.
These companies are not trying to build a general assistant for everyone. Instead, they are applying artificial intelligence to specific industries where customers already spend enormous amounts of money.
AlphaSense serves financial and business research teams. Clay focuses on sales and go-to-market work. EliseAI automates communication and administrative work in housing and healthcare. Norm AI focuses on legal and compliance workflows, while Basis targets accounting. Rogo serves finance, Tennr works on healthcare referrals, Hebbia supports document-heavy professional analysis, and Valence applies AI to employee coaching.
That pattern fits New York unusually well.
The city has dense concentrations of banks, hedge funds, private equity firms, law firms, accounting firms, hospitals, advertising agencies, insurers, media companies, real estate operators, and large corporate headquarters.
These businesses create huge amounts of expensive knowledge work, which is exactly where AI can deliver measurable economic value.
New York therefore does not need to copy Silicon Valley’s AI model. Its strongest advantage may come from building AI companies that sit directly inside the industries the city already dominates.
The NYC AI Momentum Index
Valuation gives us one view of scale, but it does not fully capture momentum.
A mature company with a large valuation may have raised its last round several years ago, while a younger company can move from almost nothing to a multi-billion-dollar valuation in a much shorter period.
To compare those situations more fairly, NYC Tech Journal created a simple quantitative framework called the NYC AI Momentum Index.
How the Index Works
The index uses four public variables.
| Factor | Weight | Why it matters |
|---|---|---|
| Latest known valuation | 40% | Measures current scale |
| Total disclosed funding | 25% | Measures depth of investor backing |
| Capital velocity | 20% | Measures funding relative to company age |
| Financing recency | 15% | Rewards recent funding activity |
Each company is ranked relative to the rest of the dataset on each variable. Those rankings are converted into percentile-style scores before applying the weighting.
This approach prevents a single extremely large number from dominating the entire analysis.
The index is not designed to measure actual revenue growth because most private companies do not release enough consistent financial data for that kind of comparison. Instead, it measures publicly visible scale and financing momentum.
Where real operating data is available, we discuss it separately.
NYC AI Momentum Index Rankings
| Rank | Company | Momentum score |
|---|---|---|
| 1 | Cyera | 98.0 |
| 2 | AlphaSense | 90.0 |
| 3 | Runway | 79.3 |
| 4 | Modal | 77.7 |
| 5 | General Intuition | 75.0 |
| 6 | Norm AI | 60.3 |
| 7 | Hugging Face | 54.7 |
| 8 | EliseAI | 54.0 |
| 9 | Clay | 44.0 |
| 10 | Basis | 38.5 |
| 11 | Rogo | 34.3 |
| 12 | Mirage | 33.3 |
| 13 | Hebbia | 29.8 |
| 14 | Tennr | 20.3 |
| 15 | Valence | 10.7 |
The results highlight an important difference between company size and company momentum.
Hugging Face, for example, remains one of the most strategically important AI companies in the world, yet its last major priced financing occurred in 2023. That reduces its financing-recency score even though the platform has continued to grow in importance.
General Intuition shows the opposite pattern. The company is much younger and smaller by valuation, yet it has raised an extraordinary amount of money in a short period, which pushes it much higher in the momentum ranking.
This is why no single metric should be treated as the final answer.
1. Cyera
Why Cyera Leads the Ranking
Cyera sits at the top of our dataset because it combines enormous scale with very recent financing momentum.
The company raised $600 million in June 2026 at a $12 billion valuation, making it the largest startup in our core ranking by latest completed financing valuation.
That round came only months after Cyera announced another $400 million financing at a $9 billion valuation in January 2026.
The speed of that increase is significant. In less than a year, Cyera moved through multiple multi-billion-dollar valuation levels while continuing to attract some of the largest investors in technology.
The Business Case Behind the Funding
Cyera operates in data security, a market that has become even more important because of artificial intelligence.
Businesses increasingly use sensitive company information to train models, run AI assistants, automate internal processes, and connect agents to cloud systems. As that happens, security teams need to know where sensitive information is stored, who can access it, and whether AI tools can reach data they should not be able to use.
Cyera is positioned directly inside that problem.
The company has also reported strong commercial expansion. It said revenue had increased dramatically over a two-year period while its customer base grew at a similar pace. By early 2026, the company said it was serving a meaningful portion of the Fortune 500 and had expanded its workforce to more than 1,100 employees.
Those figures are company-reported and should not be treated like audited public financial statements, but they provide useful evidence that Cyera’s valuation growth is not based only on fundraising excitement.
Why Cyera Matters for New York
Cyera proves that New York can produce major infrastructure and cybersecurity companies, not only AI applications built for industries such as finance or real estate.
That is strategically important because security sits underneath almost every serious enterprise AI project.
As companies deploy more AI, they create more data access, more automated actions, and more potential security exposure. Cyera therefore benefits from the broader AI boom even though it does not need to compete directly with companies building general-purpose foundation models.
2. AlphaSense
AlphaSense represents one of the strongest examples of New York’s traditional industry advantages combining with artificial intelligence.
The company raised $350 million in June 2026 at a $7.5 billion valuation, almost doubling its previous reported valuation.
More importantly, AlphaSense said it had passed $600 million in annual recurring revenue, up from $500 million only months earlier.
That makes AlphaSense different from many private AI companies because investors can compare its valuation with a meaningful operating metric rather than funding announcements alone.
Why AlphaSense Fits New York So Well
AlphaSense helps users search and analyze financial reports, earnings transcripts, market research, company filings, expert interviews, and other business information.
Its customers include the kinds of people New York has in enormous numbers: investors, bankers, consultants, corporate strategy teams, analysts, and executives.
These professionals already spend heavily on information.
AlphaSense does not have to convince them that research is important. Its job is to help them find the right information faster, understand it more easily, and reduce the amount of manual work required before making a decision.
That creates a clear economic case.
The Broader Lesson
AlphaSense demonstrates why vertical AI companies can become extremely large without trying to serve every possible customer.
A startup can focus on one expensive category of work, dominate that workflow, and then expand into nearby jobs, departments, and data sources.
For New York founders, this may be one of the most repeatable strategies available.
3. Runway
Runway has become one of the clearest examples of advanced AI research being built in New York rather than Silicon Valley.
The company raised $315 million in February 2026 at a valuation of approximately $5.3 billion, bringing total disclosed funding to around $860 million.
Runway first became widely known for generative video, but its ambitions have grown far beyond simple video creation.
Moving Toward World Models
Runway increasingly talks about developing world models, which are AI systems designed to understand how objects, environments, motion, and actions change over time.
That matters because video contains more than images.
It contains information about movement, cause and effect, physical interactions, and how scenes evolve. A system that learns these patterns could eventually be useful in robotics, simulation, entertainment, design, and other areas where understanding the physical world matters.
Enterprise Adoption Is Expanding
Runway has also reported strong business growth.
The company said its business more than doubled during 2026 and that net revenue retention exceeded 300%. It has also cited large enterprise customers and partnerships across technology, media, advertising, and financial services.
These operating signals suggest Runway is moving beyond being a creative tool used mainly by individual creators.
The company is increasingly becoming part of enterprise video production and content workflows.
Why New York Is a Natural Home for Runway
New York has one of the deepest concentrations of creative industries in the world.
Advertising, television, film, publishing, fashion, design, media, and corporate marketing all require large amounts of visual content.
If AI-generated video becomes part of standard commercial production, New York provides Runway with both customers and talent close to home.
4. Modal
Modal is less famous outside technical circles, but its 2026 growth makes it one of the most important New York AI startups to watch.
The company raised $355 million in May 2026 at a $4.65 billion valuation and said it had passed $300 million in annualized revenue.
Modal had also grown roughly fivefold from the previous September, according to company disclosures.
What Modal Actually Provides
Modern AI products require enormous computing resources.
Companies need access to GPUs for model training, inference, agent workloads, batch processing, reinforcement learning, and other demanding tasks.
Traditional cloud platforms can support those jobs, but many were designed before the current AI boom.
Modal is trying to build cloud infrastructure that feels more natural for AI developers.
Instead of spending large amounts of time configuring servers and managing infrastructure, developers can focus more directly on their applications.
Why Infrastructure Can Become Extremely Valuable
Infrastructure companies can benefit from the growth of many different AI categories at once.
Modal does not need to predict whether legal AI, sales AI, video generation, voice AI, or healthcare AI becomes the largest market.
If developers across all of those markets require computing infrastructure, Modal can potentially sell to all of them.
That gives the company one of the broadest opportunities in the New York AI ecosystem.
5. Hugging Face
Hugging Face is one of the hardest companies in our dataset to evaluate using ordinary startup metrics.
Its last major priced financing occurred in 2023, when the company raised $235 million at a $4.5 billion valuation.
Since then, however, Hugging Face has become one of the most important platforms in the global open-source AI ecosystem.
Developers use it to share models, datasets, applications, research, and machine-learning tools.
Why the Old Valuation May Understate Its Importance
A three-year-old private valuation can become stale quickly in a fast-moving market.
That appears especially true for Hugging Face.
Recent reports have suggested that Nvidia has explored a possible acquisition at a value far above the company’s last completed funding-round valuation.
No acquisition has been completed, so we do not treat the reported purchase price as a confirmed value.
Still, the reports show how strategically important Hugging Face has become.
Its value comes not only from software revenue but from the developer ecosystem built around the platform.
Why Hugging Face Matters for NYC
New York is often described as a vertical AI city, but Hugging Face provides an important counterexample.
It is a horizontal platform used by developers around the world.
That matters because a durable AI ecosystem needs more than applications. It also needs infrastructure, developer tools, research communities, and technical platforms that other companies depend on.
6. Clay
Clay has become one of New York’s most closely watched AI companies in sales and go-to-market software.
Its August 2025 Series C raised $100 million at a $3.1 billion valuation.
Then, in January 2026, the company completed an employee tender offer at a $5 billion valuation.
Because that second transaction was a secondary liquidity event rather than the same type of primary financing used in our central dataset, we keep Clay’s $3.1 billion primary-round valuation in the main comparison.
Even so, the $5 billion tender price is a powerful sign of investor interest.
Clay’s Revenue Growth Stands Out
Clay reported that revenue grew more than 3.5 times during 2025 and that the company reached $100 million in annual recurring revenue by December.
It also reported around 14,000 customers and enterprise net revenue retention above 200%.
These are among the strongest publicly disclosed operating metrics in the New York AI startup market.
Why Clay Is Interesting Strategically
Clay helps sales and marketing teams combine data, prospect research, enrichment, AI agents, and automated workflows.
The larger opportunity is not simply to create another sales tool.
It is to become the intelligent layer connecting many of the tools sales teams already use.
If AI can decide which prospect should be contacted, gather useful information, personalize outreach, update internal systems, and trigger the next action automatically, companies may need fewer disconnected applications.
That could make Clay part of a much larger change in the enterprise sales stack.
7. General Intuition
General Intuition is one of the youngest companies in this ranking, yet it has already attracted an extraordinary amount of capital.
The company announced $320 million in financing at a $2.3 billion valuation in June 2026.
That brought total disclosed funding to approximately $454 million only a short time after the business was launched.
This high funding velocity is one reason General Intuition ranks so strongly in our Momentum Index.
What General Intuition Is Building
The company is developing AI systems that learn actions and movement.
Its unusual advantage comes from video-game data.
General Intuition emerged from Medal, a gaming platform that accumulated large volumes of video showing what players saw and what actions they took inside games.
That combination of visual information and action data may be valuable for training models to understand how agents interact with environments.
From Games to the Physical World
The long-term ambition is much larger than gaming.
General Intuition has shown experiments involving robots and physical movement, suggesting that models trained using gaming data may eventually help machines understand real-world actions.
Investors appear to believe that possibility could become extremely valuable.
Reports in August 2026 suggested the company was already discussing another financing that could value it around $6 billion before new investment.
Because that transaction was not complete at the time of analysis, we keep the $2.3 billion completed-round valuation in our core dataset.
If the proposed financing closes near reported terms, General Intuition could quickly move much higher on this list.
8. EliseAI
EliseAI shows how vertical AI can grow by solving a large number of repetitive operational tasks inside a specific industry.
The company raised $250 million in August 2025 at a reported valuation of approximately $2.2 billion.
Its early focus was housing, where property managers deal with huge amounts of repetitive communication.
EliseAI automates work such as answering renter questions, scheduling apartment tours, handling maintenance communication, following up with prospects, and responding to residents.
The company has since expanded into healthcare.
EliseAI Is Building a Large NYC Presence
In 2026, EliseAI announced a major new headquarters in Manhattan.
The company also said its technology supports housing providers representing approximately one in six U.S. apartments.
That level of penetration suggests the company has moved well beyond the experimental phase.
A New Financing Could Change Its Ranking
Recent reports have suggested EliseAI is discussing another large round that could value the company around $3.7 billion.
The same reports have also indicated that the company reached roughly $100 million in annual recurring revenue during 2025.
Because the financing was still under discussion when this article was prepared, we do not use the proposed valuation in the main ranking.
If the deal closes, EliseAI would move closer to the upper group of New York AI startups.
9. Norm AI
Norm AI has grown unusually quickly since its founding in 2023.
The company raised a $120 million Series C in July 2026 at a $1.2 billion valuation and says it has raised more than $260 million in total.
That funding pace is one reason Norm ranks sixth in our Momentum Index even though its valuation remains far below companies such as Runway or AlphaSense.
The Compliance Problem Norm Is Trying to Solve
Large companies operate under thousands of pages of rules.
Those regulations have to be interpreted, turned into internal policies, monitored, documented, and updated whenever requirements change.
Traditionally, much of this process depends on teams of lawyers, compliance professionals, consultants, and manual review.
Norm is trying to turn more of that work into software-driven workflows.
AI can help identify relevant rules, translate them into checks, monitor company activity, and highlight areas that need attention.
Norm Is Expanding Beyond Software
The company has also taken an unusual step by operating Norm Law, an affiliated AI-native law firm.
That model could become important because AI may change professional services in two different ways.
Some startups will sell software to existing firms.
Others may build technology-driven firms that compete directly with traditional service providers.
Norm is exploring the second path as well as the first.
10. Basis
Basis is one of the clearest examples of vertical AI in New York because it focuses on a very specific profession: accounting.
The company raised $100 million in February 2026 at a $1.15 billion valuation, after much smaller seed and Series A rounds.
That financing pushed Basis into unicorn territory only a few years after launch.
Why Accounting Is Attractive for AI
Accounting contains many characteristics that make it suitable for AI automation.
A large amount of the work is repetitive, document-heavy, rules-based, and expensive.
Accountants regularly perform reconciliations, prepare journal entries, investigate differences, review tax information, study technical accounting rules, and collect evidence from multiple systems.
Basis is trying to build AI agents that can complete meaningful parts of those workflows rather than simply answer questions.
The Opportunity Is Bigger Than Cost Cutting
The accounting industry also faces a labor problem.
Firms often struggle to hire enough qualified people for the amount of work they need to complete.
That means AI does not necessarily need to replace accountants to create value.
If software helps one accountant handle a much larger workload while humans continue to review important decisions, firms can expand capacity without adding employees at the same rate.
That makes accounting one of the strongest vertical AI opportunities in the New York market.
11. Rogo
Rogo has built its business around one of New York’s most important industries: finance.
The company raised $75 million in Series C funding in January 2026 at a $750 million valuation, bringing total funding above $165 million.
Its previous major valuation had reportedly been around $350 million.
That means Rogo more than doubled its valuation in less than a year.
Why Finance Needs Specialized AI
General AI models can answer many finance questions, but financial institutions often need much more.
They work with private company data, confidential documents, specialized research databases, internal models, regulatory requirements, and sensitive workflows.
They also need answers that can be checked and traced back to reliable sources.
This creates room for specialized platforms such as Rogo.
The company is trying to build an AI system designed specifically around the work of bankers, investors, analysts, and other finance professionals.
The New York Advantage
Rogo benefits from being located close to its buyers.
Many of the world’s largest banks, hedge funds, private equity firms, asset managers, and investment professionals work within a relatively small area of Manhattan.
That allows a company such as Rogo to learn from users quickly, build industry relationships, and sell into large institutions without needing to create a market from scratch.
12. Hebbia
Hebbia was one of the early companies to show how AI could help knowledge workers analyze very large collections of documents.
Its Matrix product allowed users to ask questions across many files while organizing the results into structured formats that were easier to review.
The company raised $130 million in 2024 at a valuation of around $700 million.
At the time, reports suggested Hebbia had reached roughly $13 million in annual recurring revenue and had grown rapidly during the previous 18 months.
Competition Is Becoming Much Stronger
Hebbia now operates in a much more crowded market.
Financial and professional-services users can choose from general-purpose AI models, specialist research systems, enterprise search platforms, internal AI tools, and vertical products designed for very specific tasks.
Several competitors have also adopted interfaces and workflows similar to the ones Hebbia helped popularize.
The company has responded by launching a major new version of Matrix.
Early pilot data reported by the company suggests users are taking more actions and engaging more frequently with the updated system.
The next challenge will be turning that product advantage into a durable competitive position as the market becomes more crowded.
13. Tennr
Tennr is applying artificial intelligence to one of the most complicated administrative problems in healthcare: referrals.
The company raised $101 million in Series C funding in June 2025 at a $605 million valuation.
That round followed a $37 million Series B less than a year earlier and brought total funding to roughly $160 million.
Why Referrals Are a Major Problem
Healthcare referrals often involve a messy chain of documents, phone calls, faxes, insurance details, medical records, scheduling work, and follow-up communication.
Staff members may need to determine whether a patient qualifies for care, whether information is missing, whether an insurance rule applies, and which provider should receive the referral.
When the process breaks, patients can fall through the cracks.
Tennr uses AI to read incoming information, organize documents, identify missing details, and help move referrals through the system.
Why This Fits New York
Healthcare is another industry where New York has enormous scale.
The city contains major hospitals, insurers, medical groups, research institutions, healthcare investors, and technology talent.
That creates a large local customer base for specialized healthcare AI companies.
Tennr shows that New York’s vertical AI opportunity extends well beyond finance and professional services.
14. Mirage
Mirage became widely known through Captions, its AI-powered video platform.
The company raised $60 million in 2024 at a $500 million valuation and later completed another $75 million growth financing in 2026, bringing total funding above $175 million.
Captions has also expanded significantly, with the company reporting more than 20 million global users and hundreds of millions of videos created on the platform.
From Video Editing to AI Creation
Mirage’s ambitions have moved beyond adding captions to videos.
The company is now developing tools and models that help users create, edit, and produce video using artificial intelligence.
This places it inside a large and increasingly competitive market that includes social video, advertising, marketing, education, entertainment, and creator tools.
Mirage is not trying to build exactly the same product as Runway.
Runway operates closer to the frontier of generative video and world-model research, while Mirage focuses more directly on creator and business workflows.
That distinction gives both companies room to grow.
15. Valence
Valence is smaller than most of the companies in our core ranking, but it represents another interesting enterprise AI category.
The company develops Nadia, an AI coaching platform designed for employees and managers.
Valence raised $50 million in Series B funding in September 2025, bringing total financing to roughly $80 million.
Available financing data places the company’s valuation at approximately $265 million.
Why AI Coaching Could Become Important
Businesses already spend large amounts of money on leadership training, employee development, management coaching, and human resources programs.
Traditional human coaching can be valuable, but it is expensive and therefore often reserved for senior employees.
AI changes those economics.
If a company can give thousands of managers access to personalized coaching at a much lower cost, coaching may become available to far more workers.
The main question is whether AI coaching develops into a strong stand-alone software category or becomes a feature inside broader HR platforms.
Valence is betting that the category will be large enough to support an independent company.
One More NYC AI Company Worth Watching: Regal
Regal sits just outside our scored dataset because its latest private valuation is less transparent than the values available for the companies above.
It still deserves attention.
The company was founded in New York in 2020 and has raised approximately $82 million, including a $40 million financing announced in 2024.
Regal builds AI voice agents for customer service and sales workflows.
The company says its customers have processed hundreds of millions of calls and agent-driven workflows using its platform.
Why Voice AI Could Become a Large Category
Telephone work remains expensive for businesses.
Customer support, sales follow-up, appointment scheduling, collections, lead qualification, and other phone-based tasks still require enormous amounts of human labor.
AI voice agents could reduce that cost while allowing businesses to respond to customers at any hour.
If enterprise adoption continues to increase, Regal could become one of New York’s more important AI companies.
A future priced financing round would also make it easier to compare Regal directly with the companies in our core dataset.
What the Dataset Tells Us About New York’s AI Advantage
Looking at these companies individually helps explain who is growing.
Looking at them together explains why New York is becoming such an important AI market.
New York Is Winning Where AI Meets Expensive Human Work
The strongest theme across the dataset is not chatbots.
It is labor productivity.
Investment analysts are expensive. Lawyers are expensive. Accountants are expensive. Sales teams are expensive. Healthcare administrators, security engineers, consultants, property-management teams, and corporate managers are also expensive.
When AI allows those workers to complete more work in less time, businesses can justify paying significant amounts for the software.
This helps explain why vertical enterprise AI accounts for nine of the 15 companies in our dataset.
Infrastructure Still Captures the Largest Share of Value
Only three companies in our infrastructure and security category account for roughly 45.3% of total valuation in the dataset.
Those companies are Cyera, Modal, and Hugging Face.
The reason is straightforward.
Infrastructure can support many different applications at the same time.
Modal can provide compute to companies building legal software, video systems, agents, healthcare applications, and sales tools.
Hugging Face can serve thousands of developers working across completely different industries.
Cyera can sell security to almost any large business using sensitive data.
Vertical AI can become enormous, but infrastructure benefits from serving multiple markets at once.
Frontier AI Is No Longer Only a West Coast Story
Runway and General Intuition are important because they are not simply putting interfaces around existing models.
They are trying to develop new AI capabilities.
Runway is pushing further into generative video and world models, while General Intuition is exploring models that understand actions, movement, and physical environments.
Together with Modal and Hugging Face, these companies show that New York is developing real technical depth alongside application-layer businesses.
The city is not only consuming AI research created elsewhere.
It is increasingly producing some of that research itself.
Finance Remains New York’s Strongest Distribution Advantage
Several companies in the dataset connect directly or indirectly to financial and professional-services work.
AlphaSense serves investment and corporate research.
Rogo is designed for finance professionals.
Hebbia helps users analyze complex documents.
Basis works with accounting teams.
Norm AI targets compliance and legal processes.
Clay supports sales teams serving many enterprise markets.
This concentration is not accidental.
New York gives these startups immediate access to sophisticated customers who already understand the problem.
That shortens the distance between product development and real-world use.
The Next Wave May Come From Companies Below $1 Billion
The largest companies naturally receive the most attention, but businesses in the $500 million to $1 billion range may offer the most interesting growth stories over the next few years.
Rogo sits around $750 million.
Hebbia’s last reported valuation was around $700 million.
Tennr reached approximately $605 million.
Mirage’s last disclosed priced valuation was around $500 million.
Each company has already reached meaningful scale, but another major round could change its position quickly.
Rogo has already demonstrated how fast that can happen by moving from around $350 million to approximately $750 million between major financings.
Funding Is Not the Same as Business Growth
It is important to treat private-company valuations carefully.
A startup can raise hundreds of millions of dollars without building a durable business.
A private valuation only reflects the price investors were willing to pay at a particular point in time.
It may rise quickly, remain unchanged for years, or fall during a later financing.
That is why the strongest companies in this article are not simply those with the biggest rounds.
The more convincing stories are the companies where several indicators are moving in the same direction.
AlphaSense has reported rising valuation and rising annual recurring revenue.
Modal disclosed more than $300 million in annualized revenue alongside its multi-billion-dollar financing.
Clay reported $100 million in ARR before completing an employee tender at a $5 billion valuation.
Runway says its business more than doubled during 2026.
Cyera has reported strong customer and revenue expansion alongside repeated financings.
Those combinations provide a stronger signal than funding alone.
How New York Businesses Should Evaluate AI Startups
Companies looking to buy AI software should not treat this ranking as a list of vendors they automatically need to use.
The largest company is not always the best choice.
A better process starts with understanding the business problem.
Begin With the Workflow
Businesses should identify tasks where employees spend large amounts of time or money.
A law firm might examine document review, legal research, compliance monitoring, or repetitive drafting.
An accounting firm might study reconciliations, journal entries, tax preparation, or technical accounting research.
A healthcare provider might examine referrals, patient communication, or scheduling.
A sales organization might focus on research, lead qualification, enrichment, and outreach.
Once the expensive workflow is clear, the business can evaluate whether AI is capable of improving it.
Demand Measurable Results
Good AI projects should eventually produce outcomes that can be measured.
That might mean reducing the time needed to complete a task.
It could mean increasing conversion rates, cutting customer wait times, speeding up an accounting close, processing more referrals, reducing manual document review, or allowing employees to handle more work.
Businesses should be cautious about pilots whose only purpose is to demonstrate that AI can generate impressive text.
The real question is whether the system changes the economics of the workflow.
Understand Where Humans Stay Involved
AI becomes more sensitive when it affects legal, financial, healthcare, accounting, security, or compliance decisions.
Businesses should know which actions the system can perform automatically and which require human approval.
They should also understand how the system records decisions, how employees can review outputs, and what happens when the AI makes a mistake.
The best enterprise AI systems may not be those that remove humans completely.
In many cases, the stronger product will be the one that knows when a person needs to make the final decision.
What NYC AI Founders Can Learn From the Fastest-Growing Companies
The same dataset also contains useful lessons for founders.
Build Where New York Already Has an Advantage
New York founders do not need to copy whatever AI category is receiving the most attention in San Francisco.
The city already has deep expertise in finance, law, healthcare, insurance, media, advertising, fashion, real estate, commerce, and professional services.
Founders who understand one of those industries may have an advantage over teams trying to learn the market from the outside.
Sell the Business Outcome
Customers rarely care about the technical architecture behind an AI product.
They care about results.
They want a process to take three hours instead of three days.
They want fewer customers to abandon a workflow.
They want employees to handle more work.
They want lower risk, higher revenue, faster decisions, or better service.
The strongest vertical AI companies sell that outcome rather than leading with technical jargon.
Own More of the Workflow
Simple AI features will become easier to copy.
A chatbot connected to a model is unlikely to create a lasting competitive advantage on its own.
The strongest companies are increasingly connecting AI to documents, databases, approvals, internal rules, customer records, communication tools, and operational systems.
That allows the AI to do more than answer questions.
It becomes part of the workflow itself.
Once a company controls an important workflow, replacing the software becomes much harder.
Companies We Deliberately Left Out
Defining a New York AI startup requires consistent rules.
A company can have a large Manhattan office without being headquartered in New York.
ElevenLabs, for example, has expanded significantly in New York, but public descriptions continue to identify the company as London-based. It therefore does not belong in a dataset focused specifically on New York-headquartered AI startups.
LangChain is another example.
The company has a New York presence, but it identifies San Francisco as its headquarters.
We also exclude businesses that are no longer independent private startups.
EvolutionIQ, for example, was acquired by CCC Intelligent Solutions in a transaction valued at approximately $730 million.
These rules make the dataset smaller, but they also make the analysis more consistent.
The Numbers That Matter Most
The entire dataset can be summarized through a small group of useful figures.
| Metric | NYC Tech Journal finding |
|---|---|
| Companies in core dataset | 15 |
| Combined latest known valuation | ~$46.72B |
| Combined disclosed funding | ~$7.99B |
| Median valuation | ~$2.2B |
| Median funding | ~$260M |
| Companies worth at least $1B | 10 |
| Vertical enterprise AI companies | 9 of 15 |
| Top five share of valuation | ~72.7% |
| Top five share of disclosed funding | ~72.9% |
| Infrastructure/security share of valuation | ~45.3% |
| Vertical enterprise AI share of valuation | ~37.4% |
| Creative/frontier AI share of valuation | ~17.3% |
Another figure is worth noting.
Ten of the 15 companies completed their latest major financing during 2026.
If we add only the latest disclosed 2026 financing event for each of those companies, the total reaches approximately $2.44 billion.
That figure does not represent all AI funding in New York during the year, and it does not include every financing completed by those companies.
It should therefore be treated as a lower-bound indicator rather than a complete market total.
Even so, it shows how much capital continues to move through New York’s leading AI startups.
What Could Change This Ranking Next?
Private-company rankings can shift quickly because one financing event can change a company’s position overnight.
General Intuition is the clearest example.
If its reported financing discussions near a $6 billion pre-money valuation result in a completed round, the company could move from seventh place by valuation into the upper group of New York AI startups.
EliseAI could also move significantly if its reported financing near $3.7 billion closes.
Hugging Face presents another possibility.
If an acquisition actually takes place, the company would no longer belong in a ranking of independent private startups.
Clay could also command a much higher primary valuation in its next financing given that an employee tender has already taken place at $5 billion and the company has reported $100 million in annual recurring revenue.
Meanwhile, Rogo, Tennr, Hebbia, and Mirage remain strong candidates to become the next billion-dollar AI companies in New York.
This is why the market should be measured repeatedly rather than treated as a fixed ranking.
Why New York’s AI Boom Looks Different From Silicon Valley’s
It is tempting to describe New York as the next Silicon Valley for AI.
That comparison misses the more interesting point.
New York does not need to become Silicon Valley.
Its advantage comes from the industries, talent, customers, and workflows that already exist in the city.
New York has Wall Street, major law firms, global advertising agencies, large media businesses, hospitals, real estate companies, insurers, fashion brands, accounting firms, consulting firms, and hundreds of major corporate headquarters.
These organizations employ enormous numbers of people who spend their days working with documents, data, research, communication, analysis, and decisions.
Artificial intelligence is particularly good at helping with exactly that type of work.
That creates a powerful local feedback loop.
Industry experts leave established companies and create startups.
Those startups can sell to former employers and nearby customers.
Investors see a large market and provide capital.
Successful companies attract engineers and executives.
More founders realize that New York can support major AI companies.
The ecosystem becomes stronger with every cycle.
Infrastructure companies such as Modal and Hugging Face add another layer by giving developers access to important AI tooling.
Cyera provides security.
Runway and General Intuition add more ambitious research and model development.
AlphaSense, Rogo, Norm, Basis, EliseAI, Tennr, Hebbia, Clay, and Valence connect AI directly to industries where New York already has deep expertise.
That combination is much more important than simply having a large number of startups.
It creates the foundations of an actual AI economy.
Conclusion
New York’s largest AI startups are no longer small challengers operating in the shadow of Silicon Valley.
Our 15-company dataset contains nearly $47 billion in latest known private valuation and roughly $8 billion in disclosed financing.
Cyera leads the group with a $12 billion valuation. AlphaSense has reached $7.5 billion while reporting more than $600 million in annual recurring revenue. Runway has become a major generative-video and world-model company. Modal has grown into a multi-billion-dollar AI infrastructure business. Hugging Face remains one of the most important platforms in the open AI ecosystem.
Behind them, companies such as General Intuition, Norm AI, Basis, Rogo, EliseAI, Tennr, and Hebbia are building strong positions in industries where New York already has a natural advantage.
The most important lesson from the data is not simply which startup ranks first.
It is that New York’s AI ecosystem is developing around the combination of deep technical talent and expensive real-world work.
That makes the city especially well suited to vertical AI companies that understand finance, law, accounting, healthcare, housing, sales, media, and other complex industries.
New York is also proving that it can produce infrastructure companies and advanced AI research businesses, which gives the ecosystem more depth than a collection of application startups alone.
The question is therefore no longer whether New York can become a major artificial intelligence hub.
It already is one.
The next question is how many of today’s fast-growing private companies can turn large funding rounds, rising valuations, and strong early adoption into durable businesses worth tens of billions of dollars.
Based on the direction of the market, several have a credible chance.
