As of October 2026, Latka tracks 507 AI & machine learning operationalization (MLOps) software companies with $10M–$100M in annual revenue. They have combined revenues of $13.8B and employ 98.1K people. They have raised $12B and serve 1.1B customers combined.
Every company below sells AI & machine learning operationalization (MLOps) 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.
AI & Machine Learning Operationalization (MLOps) software refers to a suite of tools and practices designed to facilitate the deployment, monitoring, and management of machine learning models in production environments. These solutions aim to streamline the entire machine learning lifecycle, enabling teams to transition from model development to operationalization more efficiently. MLOps software addresses critical stages such as model training, versioning, and continuous integration/continuous deployment (CI/CD), allowing organizations to rapidly iterate and improve their models over time. The primary use cases for MLOps software span various industries, including healthcare, finance, and retail, where organizations apply machine learning to enhance decision-making, forecasting, and operational efficiency. Typical features of MLOps platforms include automated workflows, data management tools, and model performance monitoring, which help ensure that deployed models operate optimally. Common buyer personas typically include data scientists, machine learning engineers, IT operations teams, and project managers focused on leveraging AI technologies to drive business outcomes.
Sorting: Highest -> Lowest
Showing 10 of 507 companies ranked by annual revenue.
Nanterre, Île-de-France, France
VusionGroup is the global leader in the digitalization solutions for commerce, serving over 350 large retailer groups around the world in Europe, Asia and North America. The Group develops technologies that create a positive impact on society by enabling sustainable and human-centered commerce.
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.
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.
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.
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.
Hsinchu, Hsinchu City, Taiwan
Accton Technology Corporation is a leading technology and service company providing design, development, and manufacturing services, as well as optimized AI/ML hardware and open networking solutions for premier infrastructure. Accton's mission is to build long-term partnerships through close collaboration, applying cutting-edge technologies with its experienced global workforce and delivering excellent services that are unsurpassed. For more information about Accton and its subsidiaries, please visit www.accton.com. Accton's mission can be summarized as follows: ⭐ Pioneering AI/ML hardware innovations for enhanced networking performance and efficiency ⭐ Be the leader in providing open networking solutions with best-in-class technology and quality ⭐ Meet emerging demand for new platforms, software, and services (XaaS) ⭐ Carefor all stakeholders, from investors to employees, community and society The company slogan, "Making Partnership Work," demonstrates Accton's total commitment to its partners and how it places the highest value on forming long-term partnerships that create maximum benefit for all. 🧑 Workforce: 5716 employees worldwide 📈 Consolidated Revenue for 2023: USD 2.70 billion 🔀 Total number of devices shipped in 2023: 7.14 milion We can be reached at: 🌳 CSR contact: [email protected] 🤝 Sales Contact: [email protected] 🙂 HR contact: [email protected] 💹 IR contact: [email protected] USA office Tel: +1 408 747 0994 Fax : +1 408 747 0982 Headquarters Tel: +886-(0)3-577-0270 Fax : +886-(0)3-578-0764 🌟 Follow us: https://portaly.cc/accton
San Francisco, California, United States
cloud-based machine learning-powered log analytics and monitoring solutions
Pasadena, California, United States
Near Inc. is a global data intelligence platform founded in 2012 that provides real-time information on places, people, and products. The platform uses AI and machine learning to collect and analyze data from over 1.6 billion monthly users across various sources such as mobile apps, websites, and offline data points.
Latka tracks 507 AI & machine learning operationalization (MLOps) software companies with $10M–$100M in annual revenue. Together they generate $13.8B in annual revenue and employ 98.1K people.
VusionGroup is the largest, with $98.9M in annual revenue, founded in 1992.
The average AI & machine learning operationalization (MLOps) software company in this list makes $27.3M a year, across 507 companies with reported revenue. They serve 1.1B customers combined.
Ranked by annual revenue, the leaders are VusionGroup, AiDash, Indicium, XTX Markets and IGAWorks.
The 507 AI & machine learning operationalization (MLOps) software companies with $10M–$100M in annual revenue tracked here have raised $12B in disclosed funding between them.
- The software must provide capabilities for model deployment and management in production environments. - It should enable monitoring and maintenance of machine learning models post-deployment. - The solution must facilitate collaboration among data scientists and operations teams through streamlined workflows. - It should support version control and rollback features for models. - Not just a data analytics tool; must also offer integrated machine learning lifecycle management functionalities.
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