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Top 4,322 Data Science and Machine Learning Platforms SaaS Companies in July 2026

As of July 2026, there are 4,322 SaaS companies in Data Science and Machine Learning Platforms. They have combined revenues of $53.9B and employ 458.6K people. They have raised $66.8B and serve 3.8B customers combined.

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
4,322
Revenue
$53.9B
Funding
$66.8B
Employees
458.6K

Filters

Sorting: Highest -> Lowest

Filters

Top Data Science and Machine Learning Platforms Companies

Showing 10 of 1,666 companies ranked by annual revenue.

1Lead Onion logo
Lead Onion

Portstewart, Northern Ireland, United Kingdom

Find in-market accounts at every buyer journey stage. By capturing buyer research signals across 20 distinct sources, Lead Onion gives you market-leading coverage and intelligence on your target audience. With built-in AI and sales tools, it ensures your outreach succeeds by connecting you with companies precisely when they need you.

Revenue
$1M
Customers
-
Year founded
2020
Funding
-
Team size
11
Growth
-
2Vectorize logo
Vectorize

Boulder, Colorado, United States

Vectorize is an innovative company that provides AI-powered solutions designed to enhance the processing of unstructured data and improve the efficiency of enterprise operations. It offers tools for data ingestion, vector search, and deep research applications.

Revenue
$1M
Customers
-
Year founded
2023
Funding
-
Team size
7
Growth
-
3CapixAI logo
CapixAI

United States

An AI Analyst for private capital

Revenue
$1M
Customers
-
Year founded
2022
Funding
-
Team size
6
Growth
-
4Swades AI logo
Swades AI

New York, New York, United States

AI product studio building

Revenue
$1M
Customers
-
Year founded
2023
Funding
-
Team size
5
Growth
-
5Byte Kitchen logo
Byte Kitchen

San Mateo, California, United States

Increasing restaurant profitability through our AI Operating System

Revenue
$1M
Customers
-
Year founded
2021
Funding
-
Team size
5
Growth
-
6CoLoop logo
CoLoop

London, England, United Kingdom

AI Copilot for insights & strategy

Revenue
$1M
Customers
-
Year founded
2020
Funding
-
Team size
6
Growth
-
7HyperGlue logo
HyperGlue

California, United States

Business intelligence on text

Revenue
$1M
Customers
-
Year founded
2020
Funding
-
Team size
5
Growth
-
8Handoff logo
Handoff

Miami, Florida, United States

AI estimator & agent for remodelers.

Revenue
$1M
Customers
-
Year founded
2019
Funding
-
Team size
6
Growth
-
9Downtobid logo
Downtobid

New York, New York, United States

Using AI to understand construction plans faster.

Revenue
$1M
Customers
-
Year founded
2019
Funding
-
Team size
5
Growth
-
10Sizolution logo
Sizolution

Berlin, Germany

Sizolution is an AI based SaaS for fashion ecommerce.

Revenue
$1M
Customers
2M
Year founded
2015
Funding
-
Team size
1
Growth
-

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.

Data Science and Machine Learning Platforms SaaS Companies | GetLatka