Latka logo

Top 50 Data Science and Machine Learning Platforms Companies With $1M–$5M Revenue (August 2026)

As of August 2026, Latka tracks 1,494 data science and machine learning platforms companies with $1M–$5M in annual revenue. They have combined revenues of $3.5B and employ 33.4K people. They have raised $1.9B and serve 1.7B customers combined.

Every company below sells data science and machine learning platforms to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.

What Data Science and Machine Learning Platforms Companies do

Data Science and Machine Learning Platforms are software solutions designed to facilitate the analysis, modeling, and interpretation of complex data sets using statistical and machine learning techniques. These platforms enable data scientists to build, train, and deploy machine learning models efficiently, often featuring tools for data visualization, preprocessing, and collaboration among team members. They support various workflows, including data ingestions, model development, and performance monitoring, catering to organizations aiming to leverage data-driven insights for decision-making. Typical use cases for these platforms include predictive analytics, customer segmentation, and operational optimization. They are utilized across various industries such as finance, healthcare, marketing, and technology. Common buyer personas include data scientists, data analysts, business intelligence professionals, and IT managers, who seek to extract actionable insights from data and improve business processes through advanced analytics and machine learning capabilities.

Companies
1,494
Revenue
$3.5B
Funding
$1.9B
Employees
33.4K

Filters

Sorting: Highest -> Lowest

Filters

Top Data Science and Machine Learning Platforms Companies With $1M–$5M Revenue

Showing 10 of 1,494 companies ranked by annual revenue.

1Propel PRM logo
Propel PRM

Tel Aviv, Israel

Provider of a PR productivity platform intended to increase PR agency productivity, retention and profitability. The company's platform uses CRM, pitching tools and market insights to send personalized pitches quicker, receive insights with AI and analytics, centralize media operations, narrow media lists to pitch relevant ideas and capture new market opportunities, clients to capture data-driven information about their target markets, get insights into big data analytics, improve team performance and helps them organize and track their PR efforts and find the right influencers to target.

Revenue
$5M
Year founded
2018
Funding
$6M
Team size
20
2Mindfuel logo
Mindfuel

München, Germany

Mindfuel is the pioneer of Data Product Management. We offer an AI-driven SaaS solution augmented by expert services that guide your data initiatives from idea to measurable impact. By combining the world of data science and product management, we enable data teams to:

Revenue
$5M
Year founded
2019
Funding
$3.8M
Team size
66
3Matter B2B logo
Matter B2B

Leeds, West Yorkshire, United Kingdom

We are changing the face of B2B sales and marketing by combining the brightest minds with the latest technology – using artificial intelligence and sales 4.0 methodology to deliver transformational results. We transform high impact sales and marketing initiatives by connecting offline and online journeys through the entire buying life cycle, creating a path for high-value interactions in the moments that matter.

Revenue
$5M
Year founded
2020
Team size
33
4Virtuals Protocol logo
Virtuals Protocol

United States

AIXBT is an AI agent and driven crypto market intelligence platform designed to provide token holders with a strategic edge in the rapidly evolving crypto space. Leveraging advanced narrative detection and alpha-focused analysis, AIXBT automates the process of tracking and interpreting market trends, helping users gain actionable insights. This project emphasizes integrating various data sources and platforms for comprehensive analysis and decision-making.

Revenue
$5M
Team size
45
5:probabl. logo
:probabl.

Paris, France

Probabl delivers universal technology enabling data scientists and teams to make the most of their data, leveraging the best practice in machine learning and artificial intelligence. Probabl is a spinoff from the Inria research lab and co-founded by experienced tech entrepreneurs and core-developers of scikit-learn. Probabl is the official operator of the scikit-learn brand, and its main contributor. Probabl's core mission is to develop and maintain commons for data science, from scikit-learn to a complete suite of tools and solutions for machine learning and artificial intelligence.

Revenue
$5M
Year founded
2023
Team size
45
6Excess Materials Exchange logo
Excess Materials Exchange

Amsterdam, Netherlands

The Excess Materials Exchange (EME) is an online, facilitated marketplace where companies can exchange ANY excess material B2B. We actively match supply and demand and materials with their highest reuse opportunities. In that sense, we work like a dating site for materials where we are the matchmakers. Our purpose is to eliminate the word waste from the dictionary, to create a reliable source of secondary materials, ranging from steel plates to textile fibers. We are one of the few marketplaces that facilitates transactions across sectors and industries. We matching materials with the help of AI, safely exchanging sensitive data via blockchain and spurring innovation around material reuse. We are tapped into a global knowledge network of circular economy experts. This enables companies to become more resource resilient, decrease their environmental footprint and improve their bottom line by turning their waste into wealth.

Revenue
$5M
Year founded
2018
Funding
$5M
Team size
45
7Atlas Metrics logo
Atlas Metrics

Berlin, BE, Germany

The all-in-one platform for ESG compliance and sustainability performance management. Atlas Metrics makes it easy for any organisation to measure and communicate business impact with automations, AI, secure data sharing and advanced analytics.

Revenue
$5M
Year founded
2021
Team size
45
8INTELIQUA logo
INTELIQUA

Chalandri, Attica, Greece

At INTELIQUA, we are pioneers in AI-powered Marketing Technology, dedicated to revolutionizing the way brands engage with their customers. Our mission is to support businesses drive repeat sales and foster brand loyalty by enhancing Customer Experience through AI and Customer Data Our innovative platform, Eliqua.CX, is designed to empower brands to cultivate robust first-party data, craft personalized data-driven customer experiences, and ultimately drive profitability through the cultivation of customer loyalty. With a global footprint spanning eight countries across two vibrant regions, South-Eastern Europe and the Middle East, we've been privileged to support a diverse array of businesses in their journey towards customer-centric success. At INTELIQUA, we believe that the future of marketing lies at the intersection of cutting-edge technology and genuine human connections, and we're committed to leading this charge

Revenue
$5M
Team size
45
9CyberSaint logo
CyberSaint

Boston, Massachusetts, United States

Powered by patented AI and actuarial data, CyberSaint's CyberStrong platform enables enterprises to master their cyber risk posture and drive executive alignment by automating compliance and translating cyber risk into financial terms. Fortune 50 titans, MSPs, and high-growth startups alike trade manual compliance assessments for automation, replace black-box scoring with transparent and credible cyber risk quantification, and consolidate point solutions into a single, intuitive platform.

Revenue
$5M
Year founded
2016
Team size
45
10nPlan logo
nPlan

London, England, United Kingdom

At nPlan we are building the world's first system to understand construction project planning. We make heavy use of machine learning to forecast outcomes of construction projects before the first shovel hits the ground. Our vision is that all construction projects should be built on time and budget, through a better understanding of plan outcomes. We are bringing certainty of the outcome to the industry, plan first. We will eliminate the crippling effects of poor planning and create a world where we’ve de-risked building infrastructure, enabling the construction of better buildings to help us live better lives.

Revenue
$5M
Year founded
2017
Team size
45

Frequently asked questions about Data Science and Machine Learning Platforms Companies With $1M–$5M Revenue

How many data science and machine learning platforms companies with $1M–$5M in annual revenue are there?

Latka tracks 1,494 data science and machine learning platforms companies with $1M–$5M in annual revenue. Together they generate $3.5B in annual revenue and employ 33.4K people.

Which data science and machine learning platforms company with $1M–$5M in annual revenue is the largest?

Propel PRM is the largest, with $5M in annual revenue, founded in 2018.

How much revenue does a typical data science and machine learning platforms company with $1M–$5M in annual revenue make?

The average data science and machine learning platforms company in this list makes $2.3M a year, across 1,494 companies with reported revenue. They serve 1.7B customers combined.

Who are the leading Data Science and Machine Learning platforms vendors with $1M–$5M in annual revenue?

Ranked by annual revenue, the leaders are Propel PRM, Mindfuel, Matter B2B, Virtuals Protocol and :probabl..

How much funding have data science and machine learning platforms companies with $1M–$5M in annual revenue raised?

The 1,494 data science and machine learning platforms companies with $1M–$5M in annual revenue tracked here have raised $1.9B in disclosed funding between them.

Related Artificial Intelligence Software categories

Inclusion Criteria

- Must provide comprehensive tools for data preparation, analysis, and model deployment. - Must support collaboration features for data scientists and business stakeholders. - Must include capabilities for both supervised and unsupervised machine learning. - Must allow for the integration of various data sources and formats. - Not just for analysis; must also provide tools for model training and evaluation.