ClearML
- Company typePrivate
- Founded2022
- HeadquartersBerkeley, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
ClearML firmographics
Firmographics- Name
- ClearML
- Legal name
- ClearML Inc.
- Website
- https://clear.ml
- Company type
- Private
- Founded year
- 2022
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Ownership category
- akta.pro rank
ClearML industry classification
Industry- Product category
- AI Infrastructure / MLOps Platform
- NAICS
- Software Publishers (5132), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- End-to-End MLOps & ML Platform Suites (HDAAABAA)
- akta.pro secondary industries
- End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA), Kubernetes & Container Platform Management (Private Cloud) (HDABABAC)
Keywords
Where ClearML is headquartered
LocationHeadquarters
- HQ city
- Berkeley
- HQ country
- United States
- HQ region
- North America
Offices3 records
Markets served
ClearML business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations
Revenue model
- SaaS Subscription (Community/Pro tiers): Cloud-hosted tier with per-user monthly subscription for growing AI teams. Community tier free for teams up to 3 users; Pro tier at $15/user/month plus usage-based charges for storage, API calls, and applications.
- Enterprise Licenses (Scale/Enterprise): On-premise or VPC deployment for organizations with 8+ GPUs or multiple large projects. Pricing based on GPU count and feature tier (Scale or Enterprise) with custom quotes and SLAs.
- Usage-based Consumption: Usage-based billing for cloud resources including artifact storage ($0.1/GB), metric events ($0.01/MB), API calls ($1/100K), and application runtime ($0.04/hr).
- GPU-as-a-Service for CSPs: Enables Cloud Service Providers and telecom providers to deliver secure, multi-tenant AI infrastructure with usage-based billing to their customers.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Community - Free tier for individuals and small teams up to 3 users |
| Subscription | Monthly | Pro - Growing AI teams up to 10 users at $15/user/month |
| Subscription | Pay-as-you-go | Scale - Organizations with 8-48 GPUs, VPC only |
| Subscription | Multi-year contract | Enterprise - Organizations with multiple large projects, VPC or On-prem Cluster |
Go-to-market motion3 records
Distribution channels6 records
Marketing channels8 records
ClearML product offering
Product offeringCore offering
ClearML provides an open-source, end-to-end AI infrastructure platform composed of three integrated layers: the Infrastructure Control Plane (for GPU cluster management across on-prem, cloud, and hybrid environments), the AI Development Center (for AI/ML model development, training, experiment tracking, and deployment), and the GenAI App Engine (for deploying and orchestrating LLM-powered applications). The platform is sold via tiered subscriptions (free Community, Pro, Scale, Enterprise) plus usage-based billing for cloud resources, and can be deployed as hosted SaaS, self-hosted, VPC, on-premise (including air-gapped), or hybrid.
Product overview
ClearML is an AI infrastructure platform that provides a three-layer architecture comprising the Infrastructure Control Plane for GPU cluster management, the AI Development Center for model building and training, and the GenAI App Engine for LLM deployment. The platform operates as both an open-source solution and enterprise offering, supporting deployment via hosted servers, self-hosted, VPC, on-prem (including air-gapped), or hybrid configurations. Additional modules include Platform Management Center for multi-tenant FinOps, Hyper-Datasets and Dataviews for enterprise data management, ClearML Pipelines for workflow orchestration, ClearML Agent for task execution, and GPU-as-a-Service for resource provisioning. The platform is silicon-agnostic (supporting AMD, NVIDIA, Intel, ARM), cloud-agnostic (Azure, AWS, GCP), vendor-agnostic, and supports flexible deployment across Kubernetes, bare metal, Slurm, and PBS environments.
Differentiator
Problem solved
Functional benefit
Products and services
- Infrastructure Control Plane GPU cluster management layer that connects and manages GPU resources across on-premises, cloud, and hybrid environments. Provides multi-tenancy, role-based access control (RBAC), dynamic fractional GPUs, job scheduling, quota management, and billing/chargeback capabilities.
- AI Development Center AI builders workbench providing integrated development environment for coding, testing, and deploying AI/ML models. Includes experiment tracking, dataset versioning, model repository, pipelines, CI/CD automation, hyperparameter optimization, and dashboards.
- GenAI App Engine LLM deployment and GenAI orchestration platform enabling rapid deployment of generative AI applications. Handles networking, authentication, and security while providing tools for custom model deployment, fine-tuning, vector database creation, and RAG workflows.
- Platform Management Center Centralized control plane for enterprise multi-tenant AI infrastructure management including GPU clusters. Enables IT administrators to provision compute resources per tenant, deploy AI tools with version tracking, monitor cross-tenant resource consumption, and implement real-time FinOps with chargeback capabilities.
- GPU-as-a-Service GPU provisioning and consumption solution for enterprise organizations and cloud service providers (CSPs). Enables secure multi-tenant GPU access with usage-based billing, dynamic resource management, and advanced workload management.
Quantifiable outcome
- GPU utilization improvement from 20-25% to 75%+
- +7 more outcomes
Companies that use ClearML
Customer profileNamed customers29 records
Segments10 records
Ideal customer profiles5 records
ClearML technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration46 records
AI capability11 records
Feature7 records
ClearML partnerships and signals
Strategic signalPartnerships
Six partnerships are on record, tiered core and minor.
- SUSEcorePartnership announced March 24, 2026 to accelerate secure enterprise AI infrastructure deployment through an integrated Kubernetes solution. Combines ClearML's AI infrastructure platform with SUSE's cloud-native platform (SUSE Rancher Prime) for simplified, secure AI workload deployment.
- VAST DatacoreClearML joined VAST Cosmos Community as a Technology Partner. Validated integration combines ClearML's AI Infrastructure Platform and GenAI App Engine with VAST's AI Operating System for unified data services, reducing deployment risk and accelerating time-to-value for enterprise AI operationalization.
- STMicroelectronicsminorClearML collaborates with STMicroelectronics to enhance AI development for microcontrollers, enabling embedded AI capabilities.
- CarahsoftcorePartnership to provide ClearML's MLOps platform to government agencies. Carahsoft serves as the government reseller for ClearML in the US.
- NVIDIAcoreNVIDIA partner with ClearML backed by NVIDIA and integrated deeply with NVIDIA AI Enterprise, NIM containers, DGX systems, and Dynamo. ClearML supports NVIDIA AI Enterprise license management and distributed inference capabilities.
- AMDcoreAMD partnership for GPU partitioning and utilization optimization. ClearML enhances AMD Instinct GPU partitioning to maximize utilization and centralize management for enterprise AI adoption.
Scale indicators11 records
Recent moves6 records
Expansion highlights6 records
ClearML competitors and assessment
Company assessmentDirect peers
- Weights & Biases: Weights & Biases (now part of CoreWeave) is a leading MLOps platform offering experiment tracking, model versioning, and pipeline orchestration with both open-source roots and enterprise SaaS. It is the most directly comparable competitor to ClearML's AI Development Center in target customer (data scientists and ML engineers) and product functionality (experiment tracking, dataset versioning, model registry).
- MLflow: MLflow is the open-source MLOps platform originally developed by Databricks and now widely adopted for experiment tracking, model registry, and deployment. It directly competes with ClearML's open-source Community tier and AI Development Center, particularly with data science teams evaluating vendor-neutral MLOps stacks.
- Domino Data Lab: Domino Data Lab provides an enterprise MLOps platform with centralized compute orchestration, governance, and collaboration features for regulated industries. It targets the same Fortune 500 buyer as ClearML and competes head-on for the multi-tenant, air-gapped, on-prem enterprise deployment use case.
- Comet: Comet offers an MLOps platform focused on experiment tracking, model production monitoring, and data lineage for ML teams. It competes with ClearML's experiment tracking, model repository, and AI Development Center capabilities among data science teams at mid-market and enterprise customers.
- Neptune.ai: Neptune.ai provides an experiment tracking and model registry platform for ML practitioners, with strong metadata management and collaboration features. It is comparable to ClearML's experiment tracking and dataset versioning capabilities within the AI Development Center layer.
- DataRobot: DataRobot is an enterprise AI platform offering automated machine learning, MLOps, and AI governance for large organizations. ClearML is integrated into DataRobot within Dell's agentic AI platform, but DataRobot also competes broadly with ClearML's full AI lifecycle positioning for enterprise buyers.
- Run:AI: Run:AI (acquired by NVIDIA) provides GPU orchestration and resource management for AI workloads on Kubernetes, directly competing with ClearML's Infrastructure Control Plane. As part of NVIDIA, it represents both a competitive threat and a signal that GPU orchestration is a strategically contested layer.
- Valohai: Valohai is an MLOps platform focused on reproducible model training, pipeline orchestration, and compute management for enterprise ML teams. It is directly comparable to ClearML in targeting enterprise data science teams with on-prem and hybrid deployment requirements.
Broad incumbents
- Amazon SageMaker: Amazon SageMaker is AWS's integrated ML platform covering data preparation, training, deployment, and MLOps at hyperscaler scale. As a broad incumbent, it overlaps significantly with ClearML's full stack but is bundled into the AWS ecosystem, making it the dominant competitor for cloud-native enterprise AI buyers.
- Google Vertex AI: Google Vertex AI is Google Cloud's unified AI platform offering model training, deployment, and MLOps integrated with Google Cloud services. As a broad incumbent, it competes with ClearML across the AI Development Center and GenAI App Engine for enterprises standardized on Google Cloud.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks4 records
Key highlights7 records
Customer concentration
ClearML social profiles
Digital presenceClearML financial estimates
Financial estimateRevenue estimate
Valuation estimate
ClearML leadership team
Management profileNumber of profiles
Profiles8 records
ClearML funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
ClearML M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about ClearML
What does ClearML do?
ClearML provides an open-source, end-to-end AI infrastructure platform composed of three integrated layers: the Infrastructure Control Plane (for GPU cluster management across on-prem, cloud, and hybrid environments), the AI Development Center (for AI/ML model development, training, experiment tracking, and deployment), and the GenAI App Engine (for deploying and orchestrating LLM-powered applications). The platform is sold via tiered subscriptions (free Community, Pro, Scale, Enterprise) plus usage-based billing for cloud resources, and can be deployed as hosted SaaS, self-hosted, VPC, on-premise (including air-gapped), or hybrid.
Is ClearML a public or private company?
ClearML is a private company. It is classified as venture growth investor backed and is currently operating.
When was ClearML founded?
ClearML was founded in 2022. It employs 11 to 50 people.
Where is ClearML based?
ClearML is headquartered in Berkeley, United States, in the North America region.
How does ClearML make money?
Four revenue lines are on record. SaaS Subscription (Community/Pro tiers) is the primary driver. The others are enterprise Licenses (Scale/Enterprise), usage-based Consumption and GPU-as-a-Service for CSPs.
Who are ClearML's main competitors?
Direct peers on record are Weights & Biases, MLflow, Domino Data Lab, Comet, Neptune.ai, DataRobot, Run:AI and Valohai. Broad incumbents are Amazon SageMaker and Google Vertex AI.
Does ClearML have an API?
Yes. ClearML offers an APIClient class that provides a Pythonic interface to access ClearML's backend REST API. Through an APIClient instance, users can access services including: authentication management, authorization and administration; debugging utilities; projects support for defining Projects containing tasks, models, datasets, and/or pipelines; queue management API; worker machines API for status reporting and task retrieval; events API for metrics and debug sample reporting; model management API; and Task Management API. Developer documentation is at clear.ml/docs/latest/docs/clearml_sdk/apiclient_sdk.
What industry is ClearML in?
ClearML's product category is AI Infrastructure / MLOps Platform. Its primary akta.pro industry code is HDAAABAA, End-to-End MLOps & ML Platform Suites, with a secondary code of HDAEANAA, End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management). Its NAICS code is 5132 and its SIC code is 7372.