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Top 3,360 Machine Learning Software SaaS Companies in July 2026

As of July 2026, there are 3,360 SaaS companies in Machine Learning Software. They have combined revenues of $51.8B and employ 420.9K people. They have raised $68.6B and serve 2.9B customers combined.

Machine Learning Software encompasses tools and applications that enable systems to learn from data and improve their performance over time without explicit programming. These solutions often utilize algorithms and statistical models to analyze patterns, make predictions, and automate decision-making processes across various domains. Common use cases include predictive analytics, natural language processing, image recognition, and anomaly detection. Commonly adopted in sectors such as finance, healthcare, marketing, and IT, machine learning software is primarily used by data scientists, business analysts, and IT professionals. Typical features include data preprocessing, model training, evaluation, and deployment, which facilitate the integration of machine learning capabilities into existing workflows. By leveraging large datasets, organizations can enhance operational efficiency, improve customer experiences, and make better-informed strategic decisions.

Companies
3,360
Revenue
$51.8B
Funding
$68.6B
Employees
420.9K

Filters

Sorting: Highest -> Lowest

Filters

Top Machine Learning Software Companies

Showing 10 of 592 companies ranked by annual revenue.

1Fal.ai logo
Fal.ai

San Francisco, California, United States

Customize, deploy, and scale models on Serverless GPUs with the world's first Python Cloud.

Revenue
$100M
Customers
-
Year founded
2021
Funding
$447M
Team size
92
Growth
-
2Quantexa Limited logo
Quantexa Limited

London, England, United Kingdom

AI data analytics platfor

Revenue
$100M
Customers
1K
Year founded
2016
Funding
$88M
Team size
872
Growth
-
3Omni Jobs. logo
Omni Jobs.

United States

OmniJobs analyses and categorises open job ads using AI so that anyone can find matching positions in seconds, regardless of their location or profession. Currently we list over +180K open jobs from +15K companies globally.

Revenue
$100M
Customers
-
Year founded
-
Funding
-
Team size
1
Growth
-
4SambaNova Systems logo
SambaNova Systems

Palo Alto, California, United States

SambaNova is the leading Enterprise AI company that delivers a full-stack infrastructure from silicon to software, specializing in machine learning and big data analytics platforms.

Revenue
$100M
Customers
-
Year founded
2017
Funding
$982M
Team size
417
Growth
-
5Moka logo
Moka

Singapore, Singapore

Provider of a Saas recruitment management system designed to make the organizational recruitment process more effective. The company's platform uses artificial intelligence enabled screening program that automatically filters candidates and makes recommendations for companies, enabling recruiters to post job listings across multiple platforms with one click, saving them from the hassle of hopping between portals and achieve better recruitment results by employing suitable candidates.

Revenue
$100M
Customers
1.1K
Year founded
2015
Funding
$146.8M
Team size
1K
Growth
-
6BigID logo
BigID

New York, New York, United States

BigID is a company that specializes in data privacy and protection. Its platform uses advanced machine learning algorithms to help organizations discover, inventory, and manage sensitive and personal data across various data sources, and comply with regulations such as GDPR and CCPA.

Revenue
$100M
Customers
116
Year founded
2016
Funding
$306.1M
Team size
500
Growth
-
7Degreed logo
Degreed

Pleasanton, United States

Degreed is an AI-driven learning platform that helps identify skill gaps, provides personalized learning, and automates learning experiences for upskilling and certification.

Revenue
$100M
Customers
-
Year founded
2012
Funding
$75.9M
Team size
565
Growth
-
8MoEngage logo
MoEngage

San Francisco, California, United States

customer engagement platform

Revenue
$100M
Customers
500M
Year founded
2014
Funding
$461M
Team size
757
Growth
-6.34%
9BUSINESSNEXT logo
BUSINESSNEXT

Noida, Uttar Pradesh, India

BUSINESSNEXT is a universe of composable enterprise solutions with a focus on banks and financial services globally. Recognized as a Leader by leading industry analysts, it leverages technology, innovation, and experience to relentlessly deliver incredible, unique, and human experiences, acing the volatile and complex business environment. BUSINESSNEXT platforms namely CRMNEXT, CUSTOMERNEXT, DATANEXT & WORKNEXT are AI and ML-driven cloud-agnostic platforms dedicated to enabling digital transformations. It comprises an enriched portfolio of hyper SaaS modular solutions that are responsive, can readily plug & play, and have superlative integration capabilities with the eco-system. BUSINESSNEXT today powers 1 million+ users across 65,000 branches and call centers, managing 1 billion end customers worldwide. BUSINESSNEXT has its USA headquarter in Raleigh, North Carolina, and its international headquarters in Noida, India. It has a footprint across 5 continents and direct offices in 14 countries across the U.S.A, MEA, and APAC.

Revenue
$98.5M
Customers
-
Year founded
2001
Funding
-
Team size
895
Growth
-
10ibi | Information Builders logo
ibi | Information Builders

Fort Lauderdale, Florida, United States

ibi™ - A global trusted leader in business intelligence, analytics, and data management solutions. Our fully-integrated platform empowers organisations to make smarter decisions, strengthen customer and supplier relationships, and drive efficiency growth. ibi solutions can be utilized together as a comprehensive solution set or separately to complement a company’s existing investments. Our modern BI approach to integrated data science allows companies to leverage their data strategies for their business needs. Headquartered in Fort Lauderdale, Florida, ibi is a proud business unit of Cloud Software Group.

Revenue
$98M
Customers
-
Year founded
1975
Funding
-
Team size
891
Growth
-

Inclusion Criteria

- Must provide tools for data preprocessing and model training - Should support both supervised and unsupervised learning methods - Must enable the deployment of trained models for real-world application - Should include analytics capabilities for model evaluation and performance tracking - Must cater to users such as data scientists, analysts, and software engineers - Not just for simple data visualization; must also enable predictive modeling and automation

Machine Learning Software SaaS Companies | GetLatka