
Domino
Founded Year
2013Stage
Series F - III | AliveTotal Raised
$228.11MMosaic Score The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.
+88 points in the past 30 days
About Domino
Domino operates in the enterprise Artificial Intelligence (AI) platform sector, providing a platform for building, deploying, and managing AI models. It focuses on collaboration, governance, and cost reduction. It serves sectors that utilize model-driven business strategies, including life sciences, financial services, manufacturing, and insurance. It was founded in 2013 and is based in San Francisco, California.
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Domino's Product Videos
ESPs containing Domino
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
The AI development platforms market offers solutions that serve as one-stop shops for enterprises that want to develop and launch in-house AI projects. Vendors in this space enable organizations to manage aspects of the AI lifecycle — from data preparation, training, and validation to model deployment and continuous monitoring — through a single platform to facilitate end-to-end model development.…
Domino named as Leader among 15 other companies, including Dataiku, Scale, and Weights & Biases.
Domino's Products & Differentiators
Domino Enterprise MLOps Platform
The Domino Enterprise MLOps platform accelerates the process of developing and productionizing data science work, reduces the cost of supporting data science teams, and mitigates regulatory risk. It enables code-first data science teams to progress through the end-to-end data science lifecycle to manage, develop, deploy, and monitor business-critical machine learning models faster. And, it does this at enterprise scale, with the requisite security, governance, compliance, reproducibility, and auditability that are required to do this safely and universally.
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Research containing Domino
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned Domino in 5 CB Insights research briefs, most recently on Oct 13, 2023.

Oct 13, 2023
The open-source AI development market map
Sep 29, 2023
The machine learning operations (MLOps) market mapExpert Collections containing Domino
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
Domino is included in 4 Expert Collections, including Tech IPO Pipeline.
Tech IPO Pipeline
568 items
Future Unicorns 2019
50 items
Artificial Intelligence (AI)
37,333 items
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Generative AI
2,951 items
Companies working on generative AI applications and infrastructure.
Domino Patents
Domino has filed 13 patents.
The 3 most popular patent topics include:
- computer printing
- data management
- graphical user interface elements

Application Date | Grant Date | Title | Related Topics | Status |
|---|---|---|---|---|
2/10/2023 | 4/1/2025 | Sensors, Engine technology, Electromagnetism, Watercraft components, Engine components | Grant |
Application Date | 2/10/2023 |
|---|---|
Grant Date | 4/1/2025 |
Title | |
Related Topics | Sensors, Engine technology, Electromagnetism, Watercraft components, Engine components |
Status | Grant |
Latest Domino News
Oct 24, 2025
By Tim King , Executive Editor at Solutions Review Solutions Review Executive Editor Tim King curated this list of notable analytics and data science news for the week of October 24, 2025. Keeping tabs on all the most relevant analytics and data science news can be a time-consuming task. As a result, our editorial team aims to provide a summary of the top headlines from the last week in this space. Solutions Review editors will curate vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy analytics and data science news items. For early access to all the expert insights published on Solutions Review, join Insight Jam , a community dedicated to enabling the human conversation on AI. Analytics and Data Science News for the Week of October 24, 2025 Databricks Announces Table Update Triggers to Automate Lakeflow Jobs Databricks released table update triggers allowing Lakeflow Jobs to automatically launch upon table changes. This event-driven approach boosts data freshness, reduces costs, and supports decentralized, responsive data pipelines aligned with data mesh principles. Dell Integrates NVIDIA, Elastic, and Starburst to Advance AI Data Platform Capabilities Dell unveiled integrations with NVIDIA, Elastic, and Starburst to strengthen its AI data platform offerings. The synergy provides enhanced AI data processing, search, and analytics capabilities to fuel enterprise AI initiatives. Domino Empowers Enterprise IT Teams to Deliver AI ROI at Scale by Maximizing Impact and Reducing Cost Domino announced solutions designed to help enterprise IT teams optimize AI project ROI, balancing impact and cost. Their platform accelerates deployment and collaboration for AI models across the enterprise, ensuring scalable, sustainable AI initiatives. MariaDB and Exasol Announce Strategic Partnership to Bring Unified High-Performance Analytics at Unprecedented Cost Efficiency MariaDB and Exasol partnered to deliver a unified analytics solution combining high performance with cost efficiency. The collaboration targets large enterprises seeking scalable, secure, and integrated data analytics capabilities. Oracle Enhances Public Safety Suite for Real-Time Data Intelligence Oracle enhanced its public safety suite, adding real-time data intelligence capabilities aimed at improving rapid response and situational awareness for emergency services and government agencies. Power BI Introduces Smarter Report Copilot Experience for Rapid Analytics Power BI upgraded its Report Copilot with enhanced AI capabilities for more intuitive visual creation, editing, and collaboration. Users benefit from better visual recommendations, expanded visual libraries, improved context awareness, and seamless iterative report building. Sisense Research Uncovers the Churn Paradox in Analytics Tool Satisfaction Sisense research revealed that while 86 percent of developers report satisfaction with their analytics tools, 82 percent have switched tools, highlighting challenges in meeting evolving enterprise needs and emphasizing the importance of continuous innovation to retain users. Expert Insights Watch this space each week as our editors will share upcoming events, new thought leadership, and the best resources from Insight Jam, Solutions Review’s enterprise tech community where the human conversation around AI is happening. The goal? To help you gain a forward-thinking analysis and remain on-trend through expert advice, best practices, predictions, and vendor-neutral software evaluation tools. NEW: Insight Jam Launches New Expert Mesh Groups in Beta Why Mesh expert group sessions? Because trying to figure this stuff out alone is slow, very messy, and full of shiny promises that don’t deliver, whitepapers gather dust, and webinars don’t get past theory. Each group is led by an expert who’s been there. You’ll sit with 8–10 peers who are wrestling with the same challenges you are, and instead of fluff. Insight Jam is Getting Set to Host Wayne Eckerson for the Jam Session ‘Six Pitfalls to Avoid When Using Power BI’ on October 24 Too many companies struggle to ensure adequate Power BI performance, optimize usage or adoption. If you are in this camp, tune in to this webinar to hear our consultants describe how to make Power BI effective at your organization with consistent usage, reporting standards and improved Power BI Performance. Drawing on real client experiences, we’ll walk through a proven methodology to uncover the root causes of common Power BI challenges and outline steps you can take to improve performance, maximize resources, and make the most of your licensing. Solutions Review is Getting Set to Host Qrvey for ‘How SaaS Companies Win with Self-Service Analytics and AI’ on November 13 Join Qrvey for an expert-led session exploring how software-as-a-service (SaaS) providers can unlock new growth, retention, and monetization opportunities through embedded self-service analytics and AI. In this event, attendees will learn how to transform their data into a true competitive advantage by empowering customers with intuitive, on-demand insights and AI-driven automation directly within their applications. On-Demand: Solutions Review Hosted Alteryx for ‘From Clean Data to Clear Insights’ on October 23 AI is most valuable when it’s seamlessly embedded into the way you already work. At Alteryx, we’ve introduced new capabilities that enhance the analytics experience with prebuilt workflows, intelligent automation, and practical AI assistance. This session will show you how these tools can help analysts and business leaders save time, improve accuracy, and deliver insights in ways that directly support business goals. On-Demand: Cher Fox Hosts the Jam Session: Making the Jump: Analyst vs. Product Owner Whether you’re an analyst considering the leap to product ownership, a product owner looking to sharpen analytical skills, or an organization investing in upskilling initiatives, this discussion provides actionable strategies for career transitions, mentorship approaches, and practical advice for succeeding in agile environments. The panelists share surprising lessons learned, common pitfalls to avoid, and how curiosity and adaptability become superpowers in navigating modern product development. SR Thought Leaders: The Unseen Backbone of Brilliance by Dr. Joe Perez Think for a moment about the majesty of a towering skyscraper piercing the clouds or the cozy family home nestled in the cozy confines of a peaceful suburb. What is the first thing that comes to mind? Perhaps its beauty, the welcoming warmth of its windows, or the sheer size of its existence. Rarely does our eye, or our initial thought, fall on what lies below – the intricate network of steel, concrete, and engineered dirt that supports it. But without this unseen backbone, the most awesome architectural marvel would be doomed to collapse. SR Thought Leaders: Use Cases Are Dead! Long Live Use Cases! by Samir Sharma The problem isn’t that use cases lack value; it’s that most organizations treat them like proof points rather than operating principles. This plays deeply into my belief and writings that the operating model is key here. Many companies chase quick wins, measure short-term ROI, and then move on to the next shiny problem. But that’s not transformation, that’s just experimentation in my opinion.
Domino Frequently Asked Questions (FAQ)
When was Domino founded?
Domino was founded in 2013.
Where is Domino's headquarters?
Domino's headquarters is located at 548 Market Street, San Francisco.
What is Domino's latest funding round?
Domino's latest funding round is Series F - III.
How much did Domino raise?
Domino raised a total of $228.11M.
Who are the investors of Domino?
Investors of Domino include UBS, Snowflake Ventures, Sequoia Capital, Coatue, Highland Capital Partners and 11 more.
Who are Domino's competitors?
Competitors of Domino include Dataiku, Anaconda, Chalk, 2021.AI, Weights & Biases and 7 more.
What products does Domino offer?
Domino's products include Domino Enterprise MLOps Platform.
Who are Domino's customers?
Customers of Domino include Lockheed Martin, Allstate and Bayer.
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Compare Domino to Competitors

Seldon specializes in machine learning operations (MLOps) solutions and focuses on the deployment and management of machine learning models for enterprise companies. The company offers a software framework that enables businesses to deploy, monitor, and manage machine learning models. Seldon's products cater to a variety of industries that require robust machine learning operations, including financial services, automotive, and insurance sectors. It was founded in 2014 and is based in Shoreditch, United Kingdom.

Dataiku specializes in Artificial Intelligence (AI) and analytics, offering a platform for enterprises to build, deploy, and manage Artificial Intelligence (AI) projects. The company provides tools for machine learning, data preparation, analytics, and governance for Artificial Intelligence (AI). It serves industries including banking, life sciences, manufacturing, and retail. It was founded in 2013 and is based in New York, New York.

DataRobot provides artificial intelligence (AI) applications and platforms within the enterprise AI suite and agentic AI platform domains. Its offerings include a suite of AI tools that integrate into business processes, allowing teams to manage AI, along with AI governance, observability, and foundational tools. It serves sectors including finance, supply chain, energy, financial services, government, healthcare, and manufacturing, and collaborates with NVIDIA and SAP. It was founded in 2012 and is based in Boston, Massachusetts.

Modzy is a production platform for machine learning that operates within the technology sector. The company offers tools and infrastructure to deploy, manage, and run machine learning models in enterprise and edge environments. Modzy's platform supports various AI applications across different industries, including manufacturing, telecom, energy and utilities, and the public sector, by providing solutions for IT architects, developers, data scientists, and executives. Modzy was formerly known as Yzdom, Inc.. It was founded in 2019 and is based in Vienna, Virginia.

H2O.ai specializes in generative artificial intelligence (AI) and machine learning. It provides a comprehensive AI cloud platform for various industries. The company offers a suite of AI cloud products, including automated machine learning, distributed machine learning, and tools for AI-driven data extraction and processing. H2O.ai caters to sectors such as financial services, healthcare, insurance, manufacturing, marketing, retail, and telecommunications. H2O.ai was formerly known as 0xdata. It was founded in 2012 and is based in Mountain View, California.
Striveworks specializes in machine learning operations (MLOps) within the technology sector. Its main offerings include a platform that allows for the rapid build, deployment, and maintenance of machine learning models, with a focus on data and model auditability, a low-code interface, and flexible deployment options. Striveworks primarily serves sectors such as physical security, national security, logistics, cybersecurity, healthcare, and finance. It was founded in 2018 and is based in Austin, Texas.
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