About ClearML

ClearML is an open-source MLOps platform that automates the machine learning lifecycle, enabling developers to build, train, and deploy AI models at scale with minimal code. It addresses the challenges of fragmented workflows and inefficient resource utilization by providing a unified solution for managing AI infrastructure across on-premise, cloud, and hybrid environments.

```xml <problem> AI/ML development and deployment are often hampered by fragmented workflows, inefficient resource utilization, and a lack of unified infrastructure management across diverse environments. This complexity leads to increased costs, slower time-to-market, and difficulties in scaling AI initiatives. </problem> <solution> ClearML provides an end-to-end MLOps platform that streamlines the entire AI lifecycle, from development to deployment, across on-premise, cloud, and hybrid environments. The platform offers three core modules: an Infrastructure Control Plane for managing and optimizing GPU resources, an AI Development Center for collaborative model building and experimentation, and a GenAI App Engine for rapid deployment of LLMs. By unifying AI infrastructure management, development, and deployment, ClearML enables organizations to maximize resource utilization, accelerate model delivery, and reduce operational overhead. The platform's modular design allows integration with existing tools, avoiding vendor lock-in and providing a customizable AI solution. </solution> <features> - **Infrastructure Control Plane:** Manages GPU resources across on-premise, cloud, and hybrid environments with multi-tenancy, quota management, and dynamic fractional GPUs. - **AI Development Center:** Provides a collaborative workbench with tools for data integration, experiment tracking, model management, and CI/CD integration. - **GenAI App Engine:** Streamlines the deployment of LLMs with built-in access control, monitoring, and tools for data ingestion and vector database creation. - **Resource Allocation Policy Management:** Enables administrators to set and enforce policies for user resource access with hierarchical quotas and cloud compute spillover. - **Model Monitoring:** Monitors live model endpoints and API calls to maximize visibility and ensure performance. - **Pipelines:** Facilitates the creation of logic-driven pipelines, job scheduling, and triggers for automated workflows. - **CI/CD Integration:** Integrates with GitOps and third-party tools for seamless integration into existing CI/CD workflows. - **Multi-tenancy:** Ensures isolated networks and storage for each tenant, mitigating the risk of data leakage. </features> <target_audience> ClearML targets AI/ML engineers, data scientists, DevOps teams, and IT professionals in enterprises, mid-market companies, and startups who are building, training, and deploying AI models at scale. </target_audience> ```

What does ClearML do?

Where is ClearML located?

ClearML is based in Tel Aviv, Israel.

When was ClearML founded?

ClearML was founded in 2016.

How much funding has ClearML raised?

ClearML has raised 13830000.

Location

Tel Aviv, Israel

Founded

2016

Funding

13830000

Employees

31 employees

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ClearML

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Executive Summary

allegro.ai 50K+

Founded 2016 – Tel Aviv, Israel

Funding

Estimated Funding

$10M+

Team (30+)

No team information available.

Company Description

Problem

AI/ML development and deployment are often hampered by fragmented workflows, inefficient resource utilization, and a lack of unified infrastructure management across diverse environments. This complexity leads to increased costs, slower time-to-market, and difficulties in scaling AI initiatives.

Solution

ClearML provides an end-to-end MLOps platform that streamlines the entire AI lifecycle, from development to deployment, across on-premise, cloud, and hybrid environments. The platform offers three core modules: an Infrastructure Control Plane for managing and optimizing GPU resources, an AI Development Center for collaborative model building and experimentation, and a GenAI App Engine for rapid deployment of LLMs. By unifying AI infrastructure management, development, and deployment, ClearML enables organizations to maximize resource utilization, accelerate model delivery, and reduce operational overhead. The platform's modular design allows integration with existing tools, avoiding vendor lock-in and providing a customizable AI solution.

Features

Infrastructure Control Plane: Manages GPU resources across on-premise, cloud, and hybrid environments with multi-tenancy, quota management, and dynamic fractional GPUs.

AI Development Center: Provides a collaborative workbench with tools for data integration, experiment tracking, model management, and CI/CD integration.

GenAI App Engine: Streamlines the deployment of LLMs with built-in access control, monitoring, and tools for data ingestion and vector database creation.

Resource Allocation Policy Management: Enables administrators to set and enforce policies for user resource access with hierarchical quotas and cloud compute spillover.

Model Monitoring: Monitors live model endpoints and API calls to maximize visibility and ensure performance.

Pipelines: Facilitates the creation of logic-driven pipelines, job scheduling, and triggers for automated workflows.

CI/CD Integration: Integrates with GitOps and third-party tools for seamless integration into existing CI/CD workflows.

Multi-tenancy: Ensures isolated networks and storage for each tenant, mitigating the risk of data leakage.

Target Audience

ClearML targets AI/ML engineers, data scientists, DevOps teams, and IT professionals in enterprises, mid-market companies, and startups who are building, training, and deploying AI models at scale.