
New York, New York, United States
retrain.ai which uses AI and machine learning to read job boards at scale and gain insight into where the job market is going.
- Revenue
- $10M
- Customers
- -
- Year founded
- 2020
- Funding
- $16M
- Team size
- 66
- Growth
- 114.64%
As of May 2026, there are 4,321 SaaS companies in Data Science and Machine Learning Platforms. They have combined revenues of $52B and employ 466.7K people. They have raised $55.6B 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.
Sorting: Highest -> Lowest
Showing 10 of 504 companies ranked by annual revenue.

New York, New York, United States
retrain.ai which uses AI and machine learning to read job boards at scale and gain insight into where the job market is going.

New York, New York, United States
Developer and provider of data science platform intended for data scientists. The company's SaaS platform which equips data science teams with high-leverage automation tools which include one-click publishing and sharing, scaling to GPUs, flexible custom environments, and eliminating hours of traditional, manual work, enabling companies to perform data science at a new level of scale, with one-click solutions.

Tulsa, Oklahoma, United States
Developer of a cloud-based emotional analytics platform created to measure and understand emotions in real-time. The company's platform combines neuroscience, cognitive technology and machine learning to understand emotions and their impact on learning, health and well-being as well as tracks, predicts and recommends customers based on relevant emotional states, enabling users to receive a new technology of artificial intelligence with empathy to improve their lives.

Beaverton, Oregon, United States
Data analytics and AI experts, specializing in project controls, delivering transformative business intelligence to elevate your success journey

New York, New York, United States
AI-scaling platform for digital transformation tailored to the insurance industry.

Dublin, California, United States
Articul8 AI is a technology company whose products transform enterprise data and expertise into powerful engines of growth, value and impact. Our full-stack GenAI platform is revolutionizing how enterprises harness their data and expertise to build expert-level Generative AI applications for their mission-critical challenges. Our products deliver enterprise-scale impact with ROI in hours to weeks. General-purpose GenAI models, while necessary, are not sufficient to deliver enterprise-specific decisioning and actioning. Our platform addresses this gap by making it straightforward for companies to build sophisticated, enterprise-scale and expert-level GenAI applications that encode their domain expertise. Our proprietary technology does the heavy lifting through autonomous decisions and actions, automated data intelligence, improved precision and relevance with industry knowledge encoded into Articul8's library of domain and task-specific models. We are purpose-built for regulated industries and meet the highest standards of compliance, data security, privacy and performance, including traceability and auditability at every step. We are trusted by leading global enterprises like AIAA, Itochu Techno-Solutions Corporation, Uptycs, AWS, NIQ, Intel and Franklin Templeton to transform their mission-critical work. We are the enterprise GenAI platform that simply works! For more information, please visit www.articul8.ai.

Nuremberg, , Germany
Innovation OS - one platform for everything innovation The ITONICS Innovation OS combines human ingenuity and machine intelligence in a collaborative innovation management software.

Luxembourg
Next Gate Tech, a Luxembourg-based FundTech, provides SaaS solutions for asset management with machine learning, data analytics, and cloud-based automation.

New York, New York, United States
Entera is the leading 3-sided marketplace focused on connecting Enterprise and Mid-Market investors, sellers and services providers in the single-family residential market. Powered by modern data science and Artificial Intelligence (AI), Entera’s marketplace offers the most seamless solution for investors to access, evaluate, transact and operate their single-family real estate investments. Backed by leading venture capital investors Goldman Sachs Growth, Bullpen Capital, and Craft Ventures, Entera is focused on delivering software innovation and offline service solutions that enable its’ investor clients to scale their operations quickly, make more market data-driven decisions confidently, and maximize financial returns. Since its inception in 2018, Entera has transacted on more than 15,000 single family homes valued at $5 Billion across 29 US markets. The company is headquartered in New York City, New York and Houston, Texas. Learn more at www.entera.ai.
- 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.
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