Domino Data Lab
Enterprise Software
Founded: 2013
Last Round Valuation: $802.58MM
Domino Data Lab is a pioneering platform that empowers data science teams to unleash the full potential of their data-driven projects. Founded in 2013 by Nick Elprin, Chris Yang, and Matthew Granade, Domino Data Lab has become a driving force behind modern data science practices, enabling organizations to accelerate their AI and machine learning initiatives. The platform provides a collaborative and scalable environment, streamlining the end-to-end data science workflow from data exploration to model deployment. With a strong focus on collaboration and reproducibility, Domino Data Lab fosters cross-functional teamwork, allowing data scientists, engineers, and business stakeholders to work seamlessly together. Armed with a comprehensive suite of tools and an infrastructure that supports various languages and frameworks, data science teams can rapidly prototype and deploy sophisticated models, making data-driven decisions and driving innovation with confidence. Domino Data Lab's commitment to empowering data scientists with cutting-edge technology and robust governance features has earned it recognition as a leader in the data science and AI ecosystem.
Domino Data Lab Overview:
Domino Data Lab is a comprehensive data science platform that revolutionizes how organizations manage, collaborate, and deploy data science projects. Founded in 2013 by Nick Elprin, Chris Yang, and Matthew Granade, the company has emerged as a prominent player in the rapidly evolving field of data science and machine learning.
At its core, Domino Data Lab provides a collaborative and scalable environment for data science teams to streamline their workflows and drive impactful results. The platform enables organizations to bring together data scientists, engineers, and business stakeholders, fostering cross-functional collaboration and encouraging knowledge-sharing across teams. This collaborative approach breaks down silos and facilitates the rapid exchange of ideas, ultimately leading to faster and more innovative data science projects.
One of the key strengths of Domino Data Lab is its commitment to reproducibility and governance. The platform maintains a detailed record of each step in the data science workflow, ensuring that every analysis, model, and decision can be traced back to its source. This feature not only enhances the transparency of data science projects but also promotes accountability and compliance, which are crucial in highly regulated industries.
Domino Data Lab supports a wide range of popular data science languages and frameworks, including Python, R, TensorFlow, and more. Its flexible infrastructure allows data scientists to seamlessly switch between tools and integrate with their preferred libraries and systems. This flexibility enhances productivity and empowers data scientists to work with the tools they are most comfortable with, promoting efficiency and reducing friction in the development process.
The platform's model deployment capabilities enable organizations to put their data science models into production quickly and efficiently. This enables businesses to operationalize the insights gained from data science projects, driving tangible value and impact. With a secure and scalable deployment environment, data science teams can confidently deploy their models and iterate on improvements, ensuring that data-driven decisions are effectively integrated into their day-to-day operations.
In addition to its technical capabilities, Domino Data Lab places a strong emphasis on providing comprehensive support and resources to its customers. The company offers training, workshops, and consulting services to help organizations optimize their data science workflows and achieve their business objectives effectively.
As a testament to its leadership in the data science space, Domino Data Lab has garnered numerous industry accolades and secured partnerships with major technology and data science players. It continues to be recognized as a leading data science platform, serving some of the world's most prominent organizations across various industries, including finance, healthcare, technology, and more.
In conclusion, Domino Data Lab's data science platform revolutionizes how organizations approach data-driven projects. By promoting collaboration, transparency, and reproducibility, the platform empowers data science teams to drive impactful insights and deploy models with confidence. With a strong commitment to innovation and customer success, Domino Data Lab remains at the forefront of the data science ecosystem, empowering businesses to harness the full potential of their data and drive meaningful results in today's data-centric world.
Founders:
Chris Yang
Matthew Granade
Nick Elprin
Top Investors:
Bloomberg Beta
Coatue Management
Dell Technologies Capital
Great Hill Partners
Highland Capital Partners
In-Q-Tel
NVIDIA
Sequoia Capital
Slow Ventures
Zetta Venture Partners
Funding History:
Date | Share Type | Amount Raised | Raised to Date | Issue Price | Post Money Valuation | Key Investors |
---|---|---|---|---|---|---|
Oct 2021 | Series F | $100MM | $228.01MM | $16.40 | $802.58MM | Great Hill Partners, NVIDIA, Coatue Management |
Jun 2020 | Series E | $43MM | $128.01MM | $8.61 | $342.99MM | Highland Capital Partners, Dell Technologies Capital |
Sep 2018 | Series D | $43.75MM | $85.01MM | $8.59 | $265.99MM | Sequoia Capital, Coatue Management |
Apr 2017 | Series C | $27MM | $41.25MM | $5.64 | $140.01MM | Bloomberg Beta, Coatue Management, Sequoia Capital |
Nov 2016 | Series B | $10.5MM | $14.25MM | $1.78 | $34.56MM | Bloomberg Beta, In-Q-Tel, Sequoia Capital |
Jul 2015 | Series A | $3MM | $3.75MM | $1.10 | $11.05MM | Bloomberg Beta, In-Q-Tel, Slow Ventures |
Mar 2015 | Series A-2 | $375K | $375K | $0.88 | $11.05MM | Bloomberg Beta, In-Q-Tel, Slow Ventures |
Mar 2015 | Series A-1 | $375K | $375K | $0.75 | $11.05MM | Bloomberg Beta, In-Q-Tel, Slow Ventures |