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Domino Data Lab

Domino Data Lab

Domino Data Lab is a machine learning platform enabling data science teams to rapidly develop and deploy models that drive breakthrough innovation

OverviewStructured DataIssuesContributors

Contents

OverviewPlatformTimelineTable: Funding RoundsTable: ProductsTable: AcquisitionsTable: SBIR/STTR AwardsTable: PatentsTable: Further ResourcesReferences
dominodatalab.com
Is a
Organization
Organization
Company
Company

Company attributes

Industry
Machine learning
Machine learning
Software development
Software development
Data science
Data science
15
Technology
Technology
‌
DevOps
MLOps
MLOps
Software
Software
Artificial Intelligence (AI)
Artificial Intelligence (AI)
Location
San Francisco
San Francisco
B2X
B2B
B2B
CEO
Nick Elprin
Nick Elprin
Founder
Matthew Granade
Matthew Granade
Nick Elprin
Nick Elprin
Chris Yang
Chris Yang
AngelList URL
angel.co/domino-data-lab
Pitchbook URL
pitchbook.com/profiles.../86622-76
Legal Name
Domino Data Lab, Inc.
Number of Employees (Ranges)
201 – 500
Email Address
support@dominodatalab.com
hello@dominodatalab.com
Phone Number
+14155702425
Number of Employees
36318
Full Address
San Francisco, CA, US
Investors
Sequoia Capital
Sequoia Capital
In-Q-Tel
In-Q-Tel
Slow Ventures
Slow Ventures
16
NVIDIA
NVIDIA
Great Hill Partners
Great Hill Partners
17
Snowflake Ventures
Snowflake Ventures
Coatue Management
Coatue Management
Zetta Venture Partners
Zetta Venture Partners
...
Founded Date
2013
Total Funding Amount (USD)
220,500,000
Latest Funding Round Date
October 5, 2021
Competitors
Wallaroo (company)
Wallaroo (company)
Civis Analytics
Civis Analytics
Quantifind
Quantifind
Uplevel
Uplevel
Mode Analytics
Mode Analytics
4Paradigm
4Paradigm
11
Spell
Spell
12
Iterative.ai
Iterative.ai
13
...
Business Model
Subscription
Board of Directors
Bryan Schreier
Bryan Schreier
Mark Gorenberg
Mark Gorenberg
‌
mac steele
‌
jay moorthi
CTO
Chris Yang
Chris Yang
Also Known As
Domino
Latest Funding Type
‌
Series F
Patents Assigned (Count)
1
Wellfound ID
domino-data-lab

Other attributes

Company Operating Status
Active
Strategic Partnerships
Appsilon Data Science
Appsilon Data Science
Latest Funding Round Amount (USD)
100,000,000
Overview

Domino Data Lab is a developer of an enterprise data science platform intended to help users develop and deploy ideas with collaborative, reusable, and reproducible analysis. The company's platform is designed to help users accelerate research, speed model deployment, and enhance collaboration for code-first data science teams. The platform is also developed to work alongside popular tools and programming languages, such as Python, R, and Julia.

The company was founded in 2013 by Nick Elprin, Matthew Granade, and Chris Yang and is headquartered in San Francisco, California. Domino Data Lab customers have included Lockheed Martin, Johnson & Johnson, Moody's Analytics, VMware, Bayer, Red Hat, and Allstate. The company has been backed by venture capital firms, including Sequoia Capital, Bloomberg Beta, Coatue Management, Dell Technologies Capital, Highland Capital Partners, and In-Q-Tel.

Platform

Domino Data Lab's MLOps platform is developed for enterprises so users can utilize data science at scale to resolve challenges around infrastructure friction, productionization challenges, and a lack of collaboration. Some features of the platform include the system of record, which allows users to capture data science work in a central repository, enabling teams to find, reproduce, and reuse work. As well, this allows users to compound knowledge with reusable code, artifacts, learnings from previous experiments, integrated project management capabilities, and the ability to replicate environments.

Example page of Domino's integrated model factory feature.

Example page of Domino's integrated model factory feature.

Another feature of the platform is called the integrated model factory, which is intended to support the data science lifecycle from ideation to production. Through this feature, users can explore data, train machine learning models, validate, deploy, and monitor these ideas and these models in production. This is intended to enable processes and workflows, which can be repeated for faster model production, automated monitoring, retraining, and republishing.

The platform offers a self-service infrastructure portal that allows users to automate time-consuming DevOps tasks required for data science to work at scale. Users can generate development sandboxes capable of being pre-loaded with preferred tools, languages, and compute power and frameworks. Further, this enables users to jump between environments, bring in data, and compare experiments to deploy and iterate upon models.

Timeline

No Timeline data yet.

Funding Rounds

Products

Acquisitions

SBIR/STTR Awards

Patents

Further Resources

Title
Author
Link
Type
Date

Data Science Blog

https://blog.dominodatalab.com/

Web

Domino Data Lab and Alexander Thamm Partner to Rapidly Scale Data Science Across DACH Region

Domino Data Lab

https://www.prnewswire.com/news-releases/domino-data-lab-and-alexander-thamm-partner-to-rapidly-scale-data-science-across-dach-region-301593134.html

Web

July 27, 2022

How Domino Data Lab's new hybrid architecture will unlock MLops potential

https://venturebeat.com/ai/how-domino-data-labs-new-hybrid-architecture-will-unlock-mlops-potential/

Web

June 22, 2022

References

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