Machine learning is no longer a new technology, and is evolving faster than ever thanks to big data and advanced algorithms. From recommending shows and movies to detecting financial fraud or optimizing logistics, machine learning is reshaping products and services across various industries. And companies that leverage it are benefiting from automation and data driven insights that are helping drive growth.
While the technology may still be advancing, many companies are already taking advantage of what ML can do. Here are some of them you should know.
Top Machine Learning Companies
- OpenAI
- Amazon Web Services
- Databricks
- DataRobot
- SoundHound
Machine Learning Companies to Know
Location: Boston, Massachusetts
What they do: DataRobot is an enterprise AI platform that automates the machine learning lifecycle, enabling organizations to build, deploy and govern predictive and generative AI models at scale. The platform combines automated machine learning (AutoML) with agentic AI capabilities, allowing teams without deep data science expertise to develop production-grade models and AI agents. By unifying the entire workflow, the platform seamlessly handles everything from data preparation and model training to final deployment and monitoring, while built-in governance and observability tools ensure continuous compliance.
Location: Santa Monica, California
Snap is the software company responsible for the Snapchat app, which enables text and visual communications among millions of monthly mobile users around the world. Lens Studio is a Snap development tool that uses machine learning models to help creators and developers build custom augmented reality experiences for Snapchat as well as other apps and websites.
Location: Boston, Massachusetts
Klaviyo’s SaaS platform comes with features intended to streamline marketing operations. Data science and machine learning power Klaviyo’s predictive analytics capabilities, which provide brands with actionable insights that can inform decisions for marketing spending and personalizations for digital customer messaging.
Location: Austin, Texas
What they do: Striveworks delivers AI-powered analysis through its cloud-native AIOps platform, which automates the machine learning lifecycle by enabling organizations to build and maintain AI models in hours rather than months. The platform combines dataset preparation, trainable models and one-click deployment capabilities for data scientists and software engineers, while maintaining model performance as operational environments change. Striveworks’ technology serves national security and commercial sectors seeking to implement AI at scale.
Location: Lenexa, Kansas
What they do: TrueML is a debt collection company that uses artificial intelligence to make the recovery process more consumer-friendly. The company relies on its machine learning platform, TrueAccord, to analyze consumer behavior and payment patterns to automatically customize the timing, channel and messaging of digital outreach. Additionally, its specialized SaaS product, Retain, allows financial institutions to bring these automated digital collection capabilities in-house to drive higher recovery rates while improving the customer experience.
Location: New York, New York
What they do: Hinge is a dating app designed to lead users to serious relationships. The company uses machine learning and AI algorithms to power its matchmaking features, including Most Compatible, which analyzes mutual dealbreakers, user activity and behavioral patterns to identify potential matches who are most-likely to connect.
Location: Redwood City, California
What they do: Liftoff helps mobile businesses acquire high-value users and maximize revenue through machine learning-driven marketing, monetization and creative solutions. The company's Cortex platform uses advanced neural-network technology to unlock patterns from massive datasets, enabling data-driven decision-making across user acquisition, ad monetization and creative optimization.
Location: San Mateo, California
Upstart is a fintech company working to innovate digital lending. For example, it applies machine learning to power digital tools designed to help lenders improve performance and customer acquisition. The technology uses algorithms to make predictions about how likely a borrower is to default and enable more accurate, informed credit decisioning.
Location: Redmond, Washington
What they do: Microsoft uses machine learning technologies to develop consumer, enterprise and developer products. On Azure, its cloud platform, the company deploys machine learning services for data preparation, model training and deployment to help businesses build and scale custom AI applications. Microsoft also embeds machine learning across its product suite, including Copilot, which now functions as an agentic platform with code generation and workflow orchestration capabilities.
Location: Washington, D.C.
What they do: Upside uses machine learning to deliver custom cashback offers for gas, groceries, restaurants and hardware stores in brick-and-mortar retail. The app’s algorithms analyze consumer behavior and purchasing patterns to calculate individualized rewards, bringing data-driven personalization to physical commerce.
Location: Helsinki, Finland
What they do: Smartly operates an AI-powered advertising platform that helps brands bolster their digital marketing operations, from streamlining ad creation to measuring ad performance. The company uses machine learning to automate ad creation and optimize spend across channels, delivering real-time performance insights. Smartly’s integrated approach connects creative and media workflows to reduce production time and improve campaign efficiency.
Location: Santa Clara, California
What they do: SoundHound, is a conversational intelligence company that uses machine learning to deliver fast, highly accurate voice recognition. Through its proprietary Speech-to-Meaning and Deep Meaning Understanding platforms, the company enables devices to process spoken language and grasp complex user intent in real time. To make this tech widely accessible, SoundHound also offers the Houndify platform, allowing developers to build and deploy custom voice assistants across the automotive, retail and hospitality industries.
Location: New York, New York
What they do: Rokt operates an AI-powered e-commerce technology platform. Using machine learning, the platform powers personalized product recommendations, upsells and targeted offers for various brands and advertisers, helping them acquire customers and maximize revenue from every transaction.
Location: Marina Del Rey, California
What they do: System1 operates a digital marketing platform powered by machine learning and AI that monetizes internet traffic through its proprietary Responsive Acquisition Marketing Platform (RAMP). Using proprietary algorithms, intent data and auctioning technology, RAMP enables customer acquisition at scale across hundreds of advertiser verticals, delivering high-intent audiences that drive strong ROI for advertisers.
Location: Pasadena, California
What they do: OpenX is a cloud-based adtech platform that leverages machine learning and AI to power programmatic advertising. The company’s core offering, OpenX IQ includes services like inventory quality scoring, audience modeling and performance optimization, enabling advertisers and agencies to make customized media buying decisions at scale.
Location: New York, New York
What they do: Canoe uses machine learning and AI to automate alternative investment data management, extracting and classifying information from unstructured documents like capital statements and investor reports. The platform enables users to streamline document collection, data extraction and workflow automation across alternative asset classes.
Location: Medford, Massachusetts
Agero provides clients in insurance and automotive industries with software and solutions for accident management, roadside assistance, post-warranty benefits programs and electric vehicle support. It collects more than 60 terabytes of data each year in order to optimize service delivery. The company says that it partners with Lyft, along with many other companies.
Location: Stamford, Connecticut
What they do: KAYAK uses machine learning and real-time data from travel service providers to power its search and recommendation capabilities. The platform helps consumers explore and compare rates for flights, hotels, car rentals and vacation packages. And in 2026, the company launched Ask AI, a conversational AI tool that combines natural language search with live-updating results, enabling travelers to plan and book trips through intuitive chat-based interactions while accessing current pricing and availability across hundreds of travel partners.
Location: Santa Monica, California
What they do: Metropolis applies computer vision and machine learning to power checkout-free payment experiences across parking and aviation facilities. The company’s Recognition Platform uses neural network-based detection and proprietary datasets to identify vehicles and passengers as they enter and exit locations, enabling direct account charging without manual payment. Metropolis’ technology also supports revenue generation for operators through dynamic pricing and real-time data insights.
Location: Mountain View, California
What they do: Google embeds machine learning across its products and cloud services through its Gemini family of AI models and enterprise platforms. Its machine learning technologies power search with AI Mode, image recognition through Nano Banana, translation and specialized tools like NotebookLM for research and Google Flow for creative workflows. For enterprises, Google Cloud also offers the Gemini Enterprise Agent Platform and custom AI model training capabilities, enabling organizations to build and govern AI agents tailored to their specific needs.
Location: Seattle, Washington
What they do: Amazon Web Services provides companies with comprehensive AI and machine learning services to solve business challenges and accelerate innovation. Key use cases include conversational AI for customer engagement through Amazon Lex, fraud detection via Amazon SageMaker and specialized fraud detection tools and automating document data extraction. AWS also provides access to generative AI through Amazon Bedrock, allowing enterprises to build applications with top foundation models.
Location: Fully Remote
What they do: Gradient AI develops solutions for the insurance industry, using AI and machine learning to support automated, accurate and profitable underwriting and claims processes. The company offers products designed to enable greater efficiency for group health providers, property and casualty providers and workers’ compensation providers.
Location: Louisville, Colorado
What they do: AMP’s automated recycling sortation solutions rely on advanced technologies like artificial intelligence, machine learning and computer vision. Customers can opt for a turnkey plant equipped with the AMP ONE system’s capabilities, or work with AMP on building a custom plant, which the company says can be ready for deployment within nine months.
Location: San Francisco, California
What they do: OpenAI develops machine learning models that power its ChatGPT chatbot, allowing it to generate text, images and audio. Meanwhile, OpenAI’s enterprise products and frontier models are available through its API and cloud platforms, allowing organizations to build their own custom AI applications.
Location: Cambridge, Massachusetts
What they do: Kensho, an S&P Global company, applies machine learning and natural language processing to structure unstructured data and extract actionable insights for decision-making. The company’s Classify platform uses AI to identify and tag specific concepts within text documents, with accuracy tuned for business and finance language. Users can submit concept definitions to train custom models with minimal labeled data, or leverage pre-built concept sets designed using S&P Global’s financial domain expertise. Kensho also provides core AI capabilities and LLM-ready data retrieval infrastructure that power generative and agentic AI systems across enterprise workflows.
Location: New York, New York
What they do: Hyperscience uses proprietary machine learning technology to automate document processing and convert unstructured content into machine-readable data. The company’s Hypercell platform is capable of extracting and classifying data from complex documents — including handwritten forms — and features integrations with major EHR systems to operates across multiple industries. In healthcare, for example, Hyperscience automates patient registration, billing, claims processing and clinical documentation to reduce administrative costs and minimize errors.
Location: Fully Remote
Dropbox offers cloud-based tools to simplify digital workflows for business teams ranging from IT to sales and marketing. The company has been working to build out its team of machine learning engineers to support efficient development, prototyping and deployment of new artificial intelligence solutions.
Location: Cambridge, Massachusetts
What they do: MORSE is a software and algorithm development company, specializing in machine learning, advanced analytics and AI test and evaluation services for national security applications. The company was selected by the Pentagon’s Joint Artificial Intelligence Center to develop AI capabilities for the U.S. military, and has since secured major contracts to modernize military data and software engineering infrastructure.
Location: Armonk, New York
What they do: IBM uses machine learning to provide automation solutions, predictive analytics and model deployment. Through its platforms IBM Watson and Watson Studio, the company helps organizations build, train and manage machine learning models. Its machine learning tools can also be used for risk detection and healthcare analytics, among other areas.
Location: Ann Arbor, Michigan
What they do: Deepgram is a machine learning company providing real-time voice AI APIs for speech-to-text, text-to-speech and voice agents. Its deep learning models power accurate transcription and audio analysis at enterprise scale across media, healthcare, customer service and contact center applications. The platform has processed over 50,000, delivering accurate, low latency solutions for conversational and batch transcription workflows.
Location: San Francisco, California
What they do: Monte Carlo offers data observability solutions that cover incident prevention, detection, alerts and resolution so companies don’t have to deal with the negative effects of data downtime. Its product includes a machine learning-enabled feature for identifying anomalies so they can be quickly addressed to maintain data quality and consistency.
Location: Boston, Massachusetts
Air Space Intelligence’s AI-enabled platform leverages simulation capabilities to enable predictive situational awareness and enhance decision making for organizations across critical industries, such as airlines, logistics providers and military operations. Its technology applies machine learning models to address real-world optimization and prediction challenges.
Location: New York, New York
What they do: Fora is a digital travel agency with AI capabilities, including Sidekick, a chatbot trained on the company’s proprietary data, and Via, an agentic AI system that automates client onboarding, payments, hotel bookings and itinerary creation. By combining machine learning with integrated booking infrastructure, Fora enables travel advisors to scale their businesses while maintaining the human expertise that travelers want.
Location: Bloomington, Minnesota
What they do: IDeaS uses machine learning and AI-powered forecasting to deliver revenue management software for businesses in the hospitality industry. Its RMS platform automates pricing recommendations and demand forecasting by analyzing vast datasets with deep-learning analytics, enabling properties to optimize revenue and occupancy.
Location: South San Francisco, California
What they do: AKASA provides generative AI solutions for the healthcare revenue cycle, automating complex administrative tasks. The company’s machine learning platform is trained on millions of clinical and financial documents to optimize health system operations. By seamlessly addressing the root causes of financial friction, AKASA helps providers prevent costly claim denials while boosting overall documentation accuracy to capture previously missed revenue.
Location: Denver, Colorado
What they do: Gusto offers software for HR, payroll and benefits management. The company’s machine learning team owns the end-to-end lifecycle of predictive modeling projects — from data analysis to model deployment — building statistical and ML models to power core product features. These experts collaborate across design, engineering and product teams to develop full-stack solutions that serve small and growing businesses.
Location: San Francisco, California
What they do: Samsara provides a connected operations cloud platform with AI-powered IoT solutions for fleet management . The company’s machine learning models are trained on video footage data, and power advanced safety features, including dash cams with collision detection and risk detection capabilities. By combining real-time telematics, computer vision and predictive analytics, Samsara enables fleets to optimize operations while proactively enhancing driver safety through automated coaching and risk identification.
Frequently Asked Questions
What kinds of industries are using machine learning today?
Machine learning is being applied across many industries, including healthcare, travel, advertising, finance, cybersecurity, education, logistics, energy and public safety. Companies use ML for tasks such as fraud detection, predictive analytics, recommendation engines, automation and customer personalization.
What are some top companies leveraging machine learning?
Some notable companies using ML include Amazon Web Services, Databricks, DataRobot, SoundHound, Unity Interactions, AKASA, Kensho Technologies, Metropolis Technologies, OpenX Technologies, KAYAK and many more.
How do companies use machine learning to improve their products or services?
Machine learning is used to enhance personalization, automate repetitive tasks, predict outcomes, improve decision-making and optimize operational efficiency. For example, KAYAK uses ML for travel recommendations and Metropolis uses it for license plate recognition to automate payments.
