Company lists · Data refreshed September 2026
Top 25 Deep learning startups impacting fintech companies based in the United States
RevenueBase identified 128 deep learning startups impacting fintech companies headquartered in the United States as of September 2026 and tracks 2,034 professional contacts across them, including 720 with verified work emails and 575 with mobile numbers. New York is the largest hub.
This list covers deep learning startups impacting fintech companies headquartered in the United States, matched on what each company actually does as described in its own words. Ranked by team size, largest first. Every row shows the company's own description, its RevenueBase Smart Search rating, and when it was last checked. Data refreshed September 1, 2026.
Published by RevenueBase, a B2B data infrastructure company. This list was built with RevenueBase Smart Search, the natural-language company search RevenueBase customers use to build their own targeted lists and unlock verified emails and direct dials at the companies on them. How these lists are built and judged.
The 25 largest deep learning startups impacting fintech companies based in the United States
Ranked by team size| # | Company | Contacts | |||
|---|---|---|---|---|---|
| 1 | 346 contacts → | ||||
Partial evidence “bluCognition enhances clients’ data and analytics capabilities by leveraging advanced AI and machine learning to transform and analyze alternative data sources - combining…” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 2 | 238 contacts → | ||||
Strong evidence “Our main planned development is deep learning algorithms, diversified markets” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 3 | 214 contacts → | ||||
Indirect evidence “Since 2009, Zest AI has been innovating and perfecting AI technology with a mission to broaden access to lending using smarter, more efficient AI.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 4 | 207 contacts → | ||||
Indirect evidence “Bud Financial (“Bud”) enriches financial data, identifying the likes of merchant, category, location and regularity of transactions, to provide actionable insights and readable…” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 5 | 168 contacts → | ||||
Indirect evidence “Founded in 2014, Scienaptic AI was built with the mission to drive financial inclusion at scale through AI-driven credit decisioning.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 6 | 67 contacts → | ||||
Indirect evidence “We believe everyone should have equitable access to meaningful credit access at affordable rates.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 7 | 66 contacts → | ||||
Indirect evidence “2nd Order Solutions (2OS) is a consulting firm that specializes in applying cutting edge analytics to the world of consumer lending.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 8 | 50 contacts → | ||||
Indirect evidence “We empower consumers with better online credit solutions.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 9 | 44 contacts → | ||||
Indirect evidence “We help financial institutions make faster, smarter credit decisions by turning raw bank transaction data into actionable insights.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 10 | 40 contacts → | ||||
Strong evidence “Point Predictive is an Ai technology company with deep expertise in building machine learning scoring models that have been widely deployed by banks and lenders.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 11 | 30 contacts → | ||||
Indirect evidence “TRUE is a software solutions company and AI lab that helps lenders harness the power of artificial intelligence to make accurately informed underwriting decisions – increasing…” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 12 | 30 contacts → | ||||
Partial evidence “The world’s most innovative lenders rely on ZestFinance to do more profitable lending through machine learning.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 13 | 28 contacts → | ||||
Partial evidence “TomoCredit, based in San Francisco, uses AI and machine learning for credit underwriting and loan decisioning.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 14 | 27 contacts → | ||||
Indirect evidence “EDGE is the leading predictive intelligence platform that leverages alternative data for consumer risk scoring and predictive behavioral mapping.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 15 | 25 contacts → | ||||
Indirect evidence “Stratyfy's AI optimizes high-stakes decisions with precision and transparency.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 16 | 24 contacts → | ||||
Indirect evidence “In the world of credit, the truth is hard to find, hidden behind inefficiencies that have unintentionally deterred and obscured it.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 17 | 23 contacts → | ||||
Indirect evidence “Accelitas® is reimagining financial access through the transformative power of data.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 18 | 22 contacts → | ||||
Partial evidence “At FinanceOps, we're leading the way in fintech innovation, offering a comprehensive AI-powered platform for both collections and back office financial operations.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 19 | 17 contacts → | ||||
Indirect evidence “At Pave, we empower consumer and SMB credit risk teams to expand approvals and grow their portfolios with AI-powered cashflow analytics.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 20 | 14 contacts → | ||||
Indirect evidence “MKT MediaStats is an AI platform that transforms millions of unstructured media and behavioral data points to actionable insights driving better investment and operational…” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 21 | 12 contacts → | ||||
Partial evidence “Upsonic products power leading financial institutions from Turkey's largest fintech companies to Fortune 500 financial services firms and the top banks in the MENA region.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 22 | 12 contacts → | ||||
Indirect evidence “Concourse builds AI agents for finance teams.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 23 | 11 contacts → | ||||
Indirect evidence “ScoreData helps businesses leverage their data to dramatically improve the quality of their engagement with their customers.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 24 | 9 contacts → | ||||
Indirect evidence “AI-powered equity research software.” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
| 25 | 9 contacts → | ||||
Indirect evidence “Decades ago the challenge in investing was the difficulty in obtaining data and the ones who had the most data and were able to analyze it most effectively were the most…” Source: RevenueBase Database · checked Sep 1, 2026Thanks. The Data Team will review it. | |||||
RevenueBase Smart Search
RevenueBase Smart Search assesses information from a company’s LinkedIn profile, information supplied directly by the company, its website, and other publicly available sources. It uses that information to rate how closely the company relates to this list’s category: deep learning startups impacting fintech companies. Every row carries its rating and the description the rating was read from, so each one can be checked rather than taken on trust.
- Strong evidence
- The company's own public description of its business names deep learning startups impacting fintech companies.
- Partial evidence
- Its own public description names part of deep learning startups impacting fintech companies, so it works in or next to the category without describing itself that way.
- Indirect evidence
- The description shown does not name deep learning startups impacting fintech companies. The match rests on the rest of the company's public profile rather than the one sentence quoted here, so this is the rating to check first.
RevenueBase Smart Search is how these lists are built: RevenueBase's data engine and AI assemble the companies that match a category defined in a user's own words, so a list can be about what companies actually do rather than about whichever industry code they were filed under.
Showing 25 of 128 deep learning startups impacting fintech companies based in the United States
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Deep learning startups impacting fintech companies based in the United States at a glance
As of Sep 1, 2026Companies by employee count
How this list was built
Company categories are rarely black and white. RevenueBase reads each company's own description of its business to decide whether it belongs among deep learning startups impacting fintech companies, so some rows will be adjacent to the category rather than pure plays. The description and RevenueBase Smart Search rating on every row are there so you can check each match yourself.
- Source
- The RevenueBase company graph: 60 million companies and 398.9 million professional contacts resolved from primary sources, queried with RevenueBase Smart Search, the natural-language company search available to every RevenueBase user.
- What qualifies
- Companies headquartered in the United States whose own description of what they do matches “deep learning startups impacting fintech companies”. Matching reads each company's description, not its industry code or its name.
- RevenueBase Smart Search
- RevenueBase Smart Search is how this list is assembled and how each row is rated. RevenueBase's data engine and AI assess a company's LinkedIn profile, information supplied directly by the company, its website and other publicly available information, then relate it to a category defined in a user's own words. Each row is rated strong evidence (its own description names deep learning startups impacting fintech companies), partial evidence (it names part of the category) or indirect evidence (the description shown names none of it and the match rests on the rest of the company's profile). The description supporting each rating is quoted on the row.
- What we exclude
- Companies whose own description does not clearly place them among deep learning startups impacting fintech companies, and records with no verified work email. Companies headquartered outside United States are excluded even when they keep an office there.
- Match quality
- In blind human judging of this matching method, 86% of matched companies were on target. Expect roughly 1 in 7 rows to be adjacent to the category rather than a pure play. Every row shows the company's own description and its RevenueBase Smart Search rating so you can judge each match yourself. Read the full methodology: how the lists are built, how the judging worked, and what the figure means.
- Ranking
- Team size, largest first: companies are ordered by the number of professionals RevenueBase tracks at each one. Employee ranges shown are reported bands, for context.
- Verification
- Every listed company carries at least one verified work email, 720 across the full list. Contacts re-verify on a rolling cadence, and each contact's own verification date is shown inside RevenueBase.
- Refresh
- This page's figures were pulled from the company graph on September 1, 2026. Lists refresh periodically as the graph is re-checked.
- Corrections
- Wrong category, wrong headquarters, or a company that has closed? Use “Report an issue” on any row. Reports go to the RevenueBase Data Team and feed back into the company graph.
Frequently asked
What is RevenueBase Smart Search?
RevenueBase Smart Search is how RevenueBase decides which companies belong on this list and how strongly each one fits. Its data engine and AI assess a company's LinkedIn profile, information supplied directly by the company, its website and other publicly available information, then relate it to the category the list is about. Each row is rated strong evidence when the company's own description names deep learning startups impacting fintech companies, partial evidence when it names part of the category, and indirect evidence when the description shown names none of it and the match rests on the rest of the company's profile.
How many deep learning startups impacting fintech companies are there based in the United States?
RevenueBase identified 128 deep learning startups impacting fintech companies headquartered in the United States as of September 2026, matched on each company's own description of what it does rather than its industry code.
What is the largest company on this list?
Blucognition, headquartered in New York, tops this list with the largest team on record.
Which city has the most deep learning startups impacting fintech companies?
New York leads with 24 headquartered companies, followed by San Francisco (13) and Cambridge (5).
How do I get contact information for these companies?
A free RevenueBase account lets you run this exact search and work the top results, verified emails and direct dials included. Upgrading unlocks all 720 verified decision-maker contacts tracked across these 128 companies.
How current is this list?
The list refreshes periodically as the company graph is re-checked. This page's figures were pulled on September 1, 2026.
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About this data
RevenueBase is a B2B data infrastructure company. Its company graph covers 60 million companies and 398.9 million professional contacts, with emails verified on a rolling cadence rather than scraped once and left to decay. These company lists are generated directly from that graph with RevenueBase Smart Search, the same natural-language company search every RevenueBase user has: describe a market in plain words, get the companies that match, and add verified emails and direct dials for the people at them. It is the same data that powers RevenueBase's B2B data products, and a free account includes 500 credits to start. How these lists are built and judged.
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