The open-sourced solution allows enterprise data scientists, DevOps, and ML engineers to do more with their machine and deep learning projects through a single unified offering
ClearML, the only unified, open source MLOps platform, today announced it has achieved a landmark year of growth, setting new milestones in revenue, user base, and partnerships. To meet surging demand for its platform, ClearML has also announced the opening of its first dedicated office in the U.S.
Machine learning operations (MLOps) technology streamlines, continuously orchestrates, and automates ML model development, deployment, and governance, enabling the commercialization of machine learning at scale. In 2022, MLOps achieved wide scale adoption. In fact, more than 90% of ML decision makers surveyed said they already had a dedicated MLOps budget or expected to have one for 2023, according to ClearML’s MLOps in 2023: What Does the Future Hold? research report.
“MLOps tools help companies overcome the challenges and complexities of developing, managing, and deploying ML models into production,” said Moses Guttmann, CEO & Co-Founder, ClearML. “You can not decouple processes and technology – and that is why unified MLOps platforms are a game changer. They provide the continuous orchestration and automation of the entire ML lifecycle process that makes commercializing machine learning possible. Companies can seamlessly experiment, develop, deploy, monitor, and retrain models in a repeatable automated process. This helps them derive business value and innovation from their data, dramatically expediting time to market, revenue, and value.”
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ClearML was purpose-built by data scientists and ML practitioners to bring CI/CD methodology to the ML space. ClearML empowers ML teams to develop, manage, deploy, and monitor the complete ML lifecycle process from a single fully integrated platform – all with just two lines of code. With ClearML, customers significantly shorten their time-to-value and time-to-revenue, ensuring ML projects are executed successfully and make it to production efficiently. The open source platform can seamlessly integrate with any organization’s existing infrastructure and tools, allowing companies and teams a fast, frictionless customer onboarding experience. Organizations can run ClearML on any infrastructure, whether it is cloud, virtual private cloud (VPC), or on premise.
“ClearML is the world’s only unified, open source MLOps platform in a category dominated by disjointed ML stacks cobbling together with closed point solutions and fragmented semi-platforms,” said Guttmann. “Our success comes from offering a complete solution that covers all aspects of the ML lifecycle from start to finish, bridging the gap between revenue and innovation. In doing so, we are safeguarding billions of dollars in ML investments annually, ensuring their impact.”
In 2022, ClearML saw record growth, tripling its YOY revenue growth and achieving a staggering 1000% increase in new users and customers. The success was powered by several key product innovations, including:
- The launch of ClearML for Enterprise, which ClearML made widely available to all enterprise organizations, offering enterprise-ready security. ClearML for Enterprise supports SSO, role-based access, and is ISO 27001-certified. ClearML for Enterprise joins the company’s generous Free and Pro tiers.
- The release of major new features including Datasets to turn code into data stores with automatic logging and versioning for simple data management, Pipelines for building job queues and prioritization, and ClearML Deploy, a powerful CI/CD for model deployment, unifying model repository, custom pipelines, and model serving.
- New cloud compute integrations with AWS, GCP, and Genesis Cloud, enabling the rollout of ClearML Apps including Autoscalers, which automate orchestration of additional AWS or GCP compute resources as needed.
- Enhancements to ClearML’s Hyper-Datasets feature, enabling the ability to view layouts and add more information such as tags, notes and project context, while making hyper-datasets assignable to projects and searchable.
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Along with ClearML’s impressive financial and user growth, the company continued to expand on its core values of frictionless user experience and integrated open source ecosystem by adding a number of new partnerships and integrations to enhance the customer experience, interoperability, and cross-team collaboration. These partnerships include:
- Ultralytics, integrating ClearML’s open source toolkit into Ultralytics’ YOLOv5 stack, the most adopted and popular object detection library, to provide enhanced computer vision capabilities
- NVIDIA, integrating with the latest NVIDIA TAO 4.0 Toolkit release
- Genesis Cloud, bringing their 100% green energy Compute Instance available to ClearML users, and
- Aporia, to help ClearML users better monitor, explain, and improve ML models once in production
Through these partnerships, ClearML has created an ultra-integrated and interoperable, unified solution, while further innovating and improving its platform.
To meet growing demand for its offering, with today’s announcement, ClearML has also announced an ambitious global expansion, with the company now opening its first dedicated office in the U.S, expanding its U.S. commercial teams, and appointing Noam Harel as its CMO and GM, North America. ClearML anticipates headcount to double by the end of 2023. ClearML continues to expand across all departments to meet the growing global demand for its platform, with employees now based in six countries across four continents.
“With the launch of our U.S. office, we will be able to provide even better support and services to our growing global customer base, as well as expand our operations and reach even more users and customers in the North American region,” said Noam Harel, CMO and GM, North America, ClearML. “We are committed to continuing to invest in, innovate, and deliver the best possible platform and experience for our global customers.”
ClearML is available as a single platform for enterprise organizations, and as an entirely modular/a la carte offering for individual ML practitioners, academia researchers, and mid-market organizations. This allows customers to take a scalable approach to their MLOps needs. Critically, ClearML is also open source, meaning the software is freely available to all users and can be modified and seamlessly integrated with customers’ existing infrastructure and processes to fit the needs of any specific user.
