Comet Raises $50 Million Series B To Accelerate ML Development For The Enterprise

Company leaps ahead of competitors with enhanced features, UI and integrations that empower teams to manage and optimize the entire machine learning lifecycle

Comet hits 5X growth in ARR and increases global workforce by 3X in 12 months, over 150 customers include Ancestry, Etsy, Uber and Zappos

Comet, provider of the development platform for enterprise machine learning (ML) teams, announced it has raised $50 million in a series B funding round, led by OpenView, with participation from existing investors Scale Venture Partners, Trilogy Equity Partners and Two Sigma Ventures. In addition, Ofer Bengal, Founder and CEO of Redis, and Dr. Oren Etzioni, CEO at AI2, have joined Comet as strategic advisors to support the company’s mission of empowering AI builders to accelerate ML-driven business outcomes and advance data science. Funding comes amid significant product development milestones, company momentum and customer wins.

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As AI increasingly becomes a strategic differentiator for businesses, this nascent field of technology has lacked adequate tooling to support the needs of the data science and machine learning teams driving innovation. Just as DevOps solutions addressed the needs of software development and IT operations teams, MLOps aspires to provide seamless capabilities across ML model development, experiment tracking and model monitoring. Comet delivers these capabilities and facilitates monitoring, iteration and collaboration across teams.

“Comet has the key ingredients to build a large and enduring company: talented team, proven product, and a tremendous market opportunity,” said Mackey Craven, Partner at OpenView. “Comet’s product, which covers the ML lifecycle in a manner no other vendor can match, is key to the company’s explosive growth and why the world’s best AI development teams have selected Comet. This advanced technology platform enables teams to develop and deploy better machine learning models faster.”

ML Experiment Management, Model Management and Model Production Monitoring in One Platform

Comet will use the funding to continue to evolve how data science and machine learning teams work by providing a single platform they can use to manage and optimize the ML lifecycle. While other products provide either experiment tracking or model monitoring tools, Comet delivers both in one ML development platform. Combining these two, previously distinct categories provides significant value and allows customers to iterate faster from early experimentation all the way to production.

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Among the updates in Comet’s latest product release are comprehensive user interface (UI) enhancements and Comet Artifacts, for managing dataset versions across any step of the ML pipeline. The updates make it remarkably simple for data science and ML teams to manage every step of the ML lifecycle – from creation and collaboration, to testing and deployment, to reproduction and/or refinement of models over time. With the addition of sophisticated continuous integration and continuous deployment (CI/CD) integrations that further automate the process of deploying models into production, Comet’s unique combination of capabilities delivers the most complete offering in the market, one that can be deployed anywhere: on-premises, in the cloud, or a hybrid of the two.

“Machine learning can deliver outsized business returns – but only when experiments can be reliably reproduced, teams can collaborate and iterate faster and models in production can be continually monitored for optimal outcomes,” said Comet CEO and Co-founder Gideon Mendels.

“Our enterprise customers use Comet to realize the full value of their machine learning investment and move models from cost centers to profit centers. Individual users and academic teams also use Comet to track and analyze tens of millions of experiments that have the potential to innovate entire industries. Now, with our latest product enhancements, we’ve made it even easier for our customers to achieve more with machine learning.”

Growing Customer Base and 5X Growth in ARR

These announcements come as Comet has accelerated momentum in the marketplace over the past year, achieving 5X growth in annual recurring revenue (ARR) and rapidly growing customer adoption, with over 150 customers from leading businesses across industries, including Ancestry, Cepsa, Etsy, Uber, WorkFusion and Zappos. Additionally, Comet has increased its global, remote workforce by 3X over that period of time as well.

Comet continues to invest in and expand its ecosystem adding additional integrations to allow customers to leverage the best frameworks, libraries, and solutions – such as Amazon Sagemaker, Catalyst, GitLab, Google Vertex AI, Keras, New Relic, Pytorch, Scikit-learn, Spark NLP and Tensorflow. These integrations allow AI development teams to choose the best tools for their use case and make Comet’s solution the most complete, with seamless capabilities across the ML lifecycle – from model development and experimentation to monitoring models in production.

“Zappos utilizes AI to improve our products, customer satisfaction, and internal business processes,” said Kyle Anderson, Director of Software Engineering at Zappos. “Using Comet and other resources, we built an ML model that reduced the likelihood of order returns due to sizing issues by about 10%, which resulted in lower cost of returns. Comet has aided our success with ML and serves to further ML development within Zappos.”

“Uber is unquestionably a data-driven company, and Comet helps our scientists use data to deliver continuous improvements to business-critical deep learning models, leading to better service for our millions of customers across the globe,” said Olcay Cirit, Staff Research Scientist and Tech Lead at Uber AI. “We always seek out the best solutions for our needs, and Comet offers the most complete experiment tracking solution on the market. It’s brought significant value to our business.”

Comet is free for individual users, early-stage startups and academic teams, and it maintains deep connections to the data science and machine learning communities. In September, Comet welcomed two industry-leading ML-focused publications to its community: Heartbeat, a community-led publication with roots in technical content for data science, ML and deep learning practitioners; and Deep Learning Weekly, a weekly mailing that curates the best industry news, learning resources, code, research and more.

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