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Top 50 Machine Learning Software Companies With $10M–$100M Revenue (October 2026)

As of October 2026, Latka tracks 550 machine learning software companies with $10M–$100M in annual revenue. They have combined revenues of $15.7B and employ 263.1K people. They have raised $17.2B and serve 2B customers combined.

Every company below sells machine learning software 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 Machine Learning Software Companies do

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
550
Revenue
$15.7B
Funding
$17.2B
Employees
263.1K

Filters

Sorting: Highest -> Lowest

Filters

Top Machine Learning Software Companies With $10M–$100M Revenue

Showing 10 of 550 companies ranked by annual revenue.

1BUSINESSNEXT 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
Year founded
2001
Team size
895
2ibi | 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
Year founded
1975
Team size
891
3Verge Genomics logo
Verge Genomics

San Francisco, California, United States

We use human data and AI to develop better drugs faster.

Revenue
$98M
Year founded
2015
Team size
63
4Aera Technology logo
Aera Technology

Mountain View, California, United States

technology company specializing in software solutions

Revenue
$97M
Year founded
2017
Funding
$209.7M
Team size
443
5Appzen logo
Appzen

San Jose, California, United States

AppZen is a software company that provides an AI-powered platform for finance teams. The platform uses artificial intelligence and machine learning algorithms to analyze financial data and automate a range of finance-related processes, including expense management, invoice processing, and auditing. AppZen's solutions are designed to help businesses reduce financial risk, increase compliance, and streamline their finance operations. The platform provides real-time insights into financial data, enabling finance teams to make data-driven decisions and optimize their financial strategies. The company was founded in 2012 and is headquartered in San Jose, California, with additional offices in India and Canada.

Revenue
$95M
Customers
22
Year founded
2012
Funding
$100.6M
Team size
353
6AiDash logo
AiDash

San Jose, California, United States

AI-powered data analytics platform

Revenue
$94.6M
Year founded
2019
Funding
$33M
Team size
402
7Indicium logo
Indicium

New York, New York, United States

Indicium is a global data services company that provides end-to-end solutions for every stage of the data lifecycle, from strategy to execution. It is a highly specialized data & AI partner that helps enterprises solve what matters now and build what comes next through deep expertise.

Revenue
$92.8M
Year founded
2017
Team size
455
8XTX Markets logo
XTX Markets

London, England, United Kingdom

XTX Markets is a leading algorithmic trading firm which uses state-of-the-art machine learning technology to produce price forecasts and serves as a liquidity provider, partnering with exchanges and e-trading venues globally.

Revenue
$92.4M
Year founded
2015
Team size
262
9IGAWorks logo
IGAWorks

Seoul, Seoul, South Korea

아이지에이웍스는 압도적인 데이터를 기반으로 디지털 전환과 데이터 드리븐 마케팅을 위한 풀스택(Full-stack) 플랫폼과 서비스를 제공하는 Data-tech 기업입니다. 기업의 1st party data를 위한 CDP(Customer Data Platform), 모바일, TV, 커머스 등 독보적인 3rd party data 제공하는 DMP(Data Management Platform), AI 기반의 데이터 드리븐 마케팅 운영을 위한 ATD(Advertiser’s trading desk) 등 클라우드 기반의 디지털 전환 및 데이터 마케팅에 관한 전방위적 비즈니스를 펼쳐나가고 있습니다.

Revenue
$92M
Year founded
2006
Funding
$38.5M
Team size
126
10SchoolAI logo
SchoolAI

Lehi, UT, United States

SchoolAI is a Student Success Platform that makes school awesome for students by helping the people who support them understand how they're doing and why. It provides educators with the time, data, and tools to design a better, more personalized classroom experience using AI tools that adapt to how students learn best.

Revenue
$91.6M
Year founded
2021
Team size
1K

Frequently asked questions about Machine Learning Software Companies With $10M–$100M Revenue

How many machine learning software companies with $10M–$100M in annual revenue are there?

Latka tracks 550 machine learning software companies with $10M–$100M in annual revenue. Together they generate $15.7B in annual revenue and employ 263.1K people.

Which machine learning software company with $10M–$100M in annual revenue is the largest?

BUSINESSNEXT is the largest, with $98.5M in annual revenue, founded in 2001.

How much revenue does a typical machine learning software company with $10M–$100M in annual revenue make?

The average machine learning software company in this list makes $28.5M a year, across 550 companies with reported revenue. They serve 2B customers combined.

Who are the leading Machine Learning software vendors with $10M–$100M in annual revenue?

Ranked by annual revenue, the leaders are BUSINESSNEXT, ibi | Information Builders, Verge Genomics, Aera Technology and Appzen.

How much funding have machine learning software companies with $10M–$100M in annual revenue raised?

The 550 machine learning software companies with $10M–$100M in annual revenue tracked here have raised $17.2B in disclosed funding between them.

Related Artificial Intelligence Software categories

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