New York’s AI scene: The 25 companies you need to know

San Francisco nonetheless will get the headlines, however New York is operating its personal AI economic system and it’s larger than most individuals know. More than 2,000 AI startups now call the city home, backed by over $27 billion in funding since 2019 and a workforce of 40,000-plus AI professionals.

That is an business, plain and easy.

What makes New York totally different is the dearth of a single obsession. San Francisco chases basis fashions and developer tooling. New York builds AI for the industries it already dominates: finance, media, healthcare, and enterprise software program.

Less “we educated a mannequin,” extra “we automated the factor your compliance group dreaded.”

A couple of issues set this ecosystem aside:

• Density on the early stage. Manhattan now produces more seed and Series A companies in a single year than the Bay Area, 543 versus 486 by one count.
• Vertical depth over horizontal hype. Where Silicon Valley optimizes for general-purpose mannequin functionality, New York optimizes for becoming AI into finance, healthcare, and media workflows that have already got entrenched compliance and regulatory calls for.

Here are the 25 companies proving that thesis proper now, ranked loosely by relevance and momentum quite than valuation.

1. Hugging Face

Hugging Face anchors a lot of the open-source AI world from its New York base, internet hosting the mannequin hub that virtually each ML group has bookmarked in some unspecified time in the future. It is the closest factor the AI group has to a city sq., with a whole bunch of 1000’s of fashions, datasets, and Spaces hosted free of charge. 

The firm’s wager is that open infrastructure beats closed gardens long run, and to date the betting odds look respectable.

2. Runway

Runway builds multimodal generative video instruments which have shifted what “AI filmmaking” even means, with its open analysis lineage now powering inventive pipelines nicely past its personal product. It is one in every of a small variety of companies globally training its personal basis fashions quite than wrapping another person’s API. That places Runway in direct competitors with labs many occasions its measurement, which is both daring or barely unhinged, relying on the day.

3. Clarifai

Clarifai has spent over a decade in laptop imaginative and prescient, lengthy sufficient to watch the remainder of the sphere catch up to issues it was already fixing. The platform handles picture, video, and textual content recognition at enterprise scale, serving authorities and industrial purchasers who wanted production-grade imaginative and prescient fashions earlier than “AI” was a board-level agenda merchandise. 

Longevity on this business is uncommon, and Clarifai has it.

4. Two Sigma

Two Sigma applies machine learning to systematic buying and selling at a scale most quant outlets solely dream about, operating statistical fashions throughout monumental datasets to discover alerts in market noise. Founded by former technologists quite than conventional Wall Street merchants, the agency treats buying and selling as a knowledge science downside first and a finance downside second. 

It stays one of many clearest examples of New York’s edge: deep capital markets experience paired with deep ML expertise.

5. Kalshi

Kalshi makes use of AI to energy federally regulated prediction markets, and its funding trajectory tells its personal story: a $300 million Series D in October 2025, then a $1 billion Series E two months later, then another $1 billion Series F in May 2026 that pushed its valuation to $22 billion. Prediction markets let merchants wager straight on real-world outcomes, from financial information releases to cultural occasions, and Kalshi’s fashions assist value and floor these markets in actual time. 

Regulators are nonetheless determining precisely how to take into consideration this class, which makes Kalshi value watching carefully.

6. Ramp

Ramp embeds AI into company spend administration, so finance groups cease reconciling receipts by hand and begin catching wasteful spend mechanically. Its AI agents flag duplicate costs, unused software program subscriptions, and coverage violations earlier than a human even opens the expense report. 

For an business constructed on tedium, automating the tedium is all the pitch, and it’s working.

7. AlphaSense

AlphaSense mines market intelligence from earnings calls, filings, and professional transcripts, turning a analysis course of that used to take analysts days right into a search question that takes minutes. Investment banks, hedge funds, and company technique groups deal with it as a major analysis layer now, forward of the analysts who used to personal that job. 

It is an efficient reminder that essentially the most priceless AI merchandise are sometimes the boring ones individuals find yourself counting on day by day.

8. F2

F2 accelerates non-public markets diligence for personal credit score, non-public fairness, and industrial banking groups, and the company says its platform evaluates deals over 60% faster by turning unstructured deal information into investment-grade evaluation. 

Backed by NFX, Left Lane Capital, and Y Combinator, F2 is betting that the companies doing essentially the most offers can pay essentially the most for pace. Given how a lot of personal fairness nonetheless runs on PDFs and prayer, that wager seems to be sound.

9. OffDeal

OffDeal is an AI-native funding financial institution constructed for small enterprise house owners who need to promote their companies at premium costs for a fraction of typical Wall Street charges. Its AI handles the analyst-level grunt work, monetary modeling, purchaser outreach, and doc preparation, releasing human advisors to give attention to technique and negotiation. 

It is a distinct segment many assumed AI would skip totally, largely as a result of no person thought to attempt.

10. Petal

Petal applies machine learning to credit score underwriting for those who conventional credit score scores routinely ignore, utilizing money movement information as a substitute of credit score historical past alone. The method lets the corporate lengthen credit score to individuals with skinny or no credit score recordsdata, a bunch customary scoring fashions have a tendency to overlook totally. It is a helpful case examine in AI increasing entry quite than simply optimizing margins.

11. Socure

Socure verifies id at a scale that makes guide fraud checks really feel virtually quaint, combining system, doc, and behavioral alerts right into a single belief rating. Banks, fintechs, and authorities companies use it to onboard clients whereas staying forward of artificial id fraud, which has exploded alongside generative AI’s means to fabricate convincing faux paperwork. The irony of preventing AI fraud with AI detection lands on everybody within the constructing finally.

12. Forter

Forter catches e-commerce fraud in actual time by analyzing transaction patterns throughout its community of service provider purchasers, approving good orders and blocking unhealthy ones earlier than checkout completes. The firm constructed its mannequin on the concept fraud alerts are stronger in mixture throughout retailers than in isolation at any single retailer. That community impact is tough to replicate, which is strictly why it really works.

13. BigID

BigID maps and protects delicate information throughout the enterprise, which is a well mannered method of claiming it finds the non-public and controlled information your safety group forgot existed. As privateness regulation expands globally, realizing the place delicate information truly lives has turn out to be a board-level legal responsibility query quite than an IT afterthought. BigID’s platform solutions that query repeatedly as a substitute of by means of an annual audit panic.

14. Deep Instinct

Deep Instinct applies deep studying to malware prevention out of its joint New York and Tel Aviv operations, predicting and blocking threats earlier than they execute quite than detecting them after the actual fact. Traditional antivirus reacts to recognized signatures; Deep Instinct’s fashions are educated to acknowledge malicious intent in recordsdata they’re encountering for the primary time. In a risk panorama the place zero-day exploits transfer sooner than patch cycles, that distinction issues.

15. Adaptive Security

Adaptive Security has raised roughly $136 million throughout two rounds: a Series A led by Andreessen Horowitz and the OpenAI Startup Fund in April 2025, adopted by a Series B led by Bain Capital Ventures that December, constructing AI-driven defenses towards AI-generated threats like deepfake phishing and voice cloning scams. As generative AI makes social engineering assaults cheaper and extra convincing, the corporate’s pitch is that you need AI watching the door. Two funding rounds in eight months from traders, which suggests they agree this downside is barely getting worse.

16. Behavox

Behavox watches for compliance and conduct threat inside enterprise communications, scanning e-mail, chat, and voice for indicators of misconduct, collusion, or regulatory violations. Financial establishments use it to catch the type of conduct that used to floor solely after a regulator’s subpoena arrived. It is both deeply reassuring or mildly terrifying, relying on how your final Slack message reads out of context.

17. Flatiron Health

Flatiron Health turns oncology information from digital well being information into analysis that truly modifications therapy choices, partnering with most cancers facilities and pharmaceutical companies on real-world proof research. Its fashions assist establish which remedies work finest for which affected person subgroups, a query medical trials alone typically reply too slowly to matter. 

The firm proves that healthcare AI’s largest wins generally dwell in information plumbing quite than prognosis itself.

18. Oscar Health

Oscar Health builds AI straight into the medical health insurance expertise, from claims triage to member assist, attempting to repair an business well-known for opacity and frustration. Its instruments assist predict member threat earlier and route care suggestions earlier than small issues turn out to be costly ones. 

Whether AI can truly repair medical health insurance stays an open query, however Oscar is without doubt one of the few insurers prepared to take a look at it at scale.

19. Okay Health

Okay Health presents AI-driven symptom steering grounded in actual, anonymized affected person information quite than generic medical literature, evaluating a consumer’s signs towards tens of millions of comparable historic circumstances. It is a helpful first cease earlier than pressing care or the emergency room, and it’d cease you from googling your signs at 2 am and assuming the worst.

20. Spring Health

Spring Health applies AI to psychological well being advantages on the employer stage, matching staff to the correct kind of care, remedy, teaching, or treatment administration sooner than conventional referral networks handle. Its matching algorithm is constructed to cut back the trial-and-error most individuals expertise when discovering the correct therapist. 

For an business the place the typical wait time for care is measured in weeks, sooner matching alone is a significant final result.

21. Understood Care

Understood Care, contemporary out of Y Combinator, matches Medicare sufferers with AI-assisted affected person advocates who assist navigate paperwork, discover sources, and entry care, a profit that grew to become Medicare-covered solely in 2024. 

The firm cites a determine of 88% of US adults reporting issue navigating the healthcare system, and with 68 million people on Medicare, the addressable downside is big whatever the actual quantity. It is a clear instance of coverage change creating room for a genuinely new AI-enabled service class.

22. Datadog

Datadog has constructed AI-assisted observability into the spine of how engineering teams monitor manufacturing techniques, utilizing machine studying to detect anomalies and predict incidents earlier than they trigger outages. 

As infrastructure has grown extra distributed and tougher to motive about manually, Datadog’s fashions take over the sample recognition work that now exceeds human scale. It is infrastructure AI that stays invisible to most finish customers whereas each engineering group depends on it day by day.

23. Bloomberg

Bloomberg educated its personal domain-specific language mannequin on a long time of proprietary monetary information, betting {that a} mannequin constructed on its corpus would outperform general-purpose alternate options on monetary duties. The firm has the type of information moat that took 40 years to construct, the type of benefit cash alone struggles to purchase. 

It is a reminder that incumbents with deep proprietary information nonetheless have an actual structural benefit within the AI period.

24. Yext

Yext applies AI to search and model solutions throughout the online, serving to companies management how their data seems when clients ask AI assistants and search engines like google questions on them. As generative AI search reshapes how individuals discover companies, Yext’s pitch has shifted from managing listings to managing how AI itself describes a model. 

That shift from search engine optimization to what some are calling “reply engine optimization” is changing into its personal self-discipline quick.

25. Dataminr

Dataminr scans the open internet in actual time, from social media to public sensors, to floor breaking occasions earlier than most newsrooms or company safety groups catch wind of them. 

Its AI flags every thing from pure disasters to safety incidents inside minutes of the primary public sign showing on-line. For organizations the place minutes of advance warning translate into actual security and monetary outcomes, that pace is all the product.

Want to see this thesis in motion?

An excellent chunk of this checklist lives on the intersection of finance and AI, and that intersection will get its personal stage this October. The Agentic AI in Financial Services Summit lands in New York on October 1, 2026, bringing collectively engineers, threat leaders, and area specialists from companies together with Citi, BNY Mellon, T. Rowe Price, and Fitch Group.

Benefit from the next:

• A grounded view of what is working, from structure to analysis
• A benchmark towards deployed techniques, on governance and inference
• A direct line into the regulatory debate, the place compliance meets engineering
• A sharper community of engineers and leaders constructing institution-grade AI