ClearML

ClearML AI Infrastructure Platform is an end-to-end AI infrastructure solution that unifies development, deployment, and management of AI workloads at enterprise scale. It provides a three-layer stack: Infrastructure Control Plane for GPU resource management across on‑premises, cloud, and hybrid environments; AI Development Center for a robust, cloud-like IDE and MLOps tooling; and GenAI App Engine for rapid GenAI deployment with secure, scalable LLM hosting. The platform emphasizes multi-tenancy, access control, cost optimization, and streamlined workflows from model development to production deployment.

How ClearML Works

1. Infrastructure Control Plane connects and manages GPU clusters across environments, offering multi-tenant access, quota management, and dynamic fractional GPUs. It enables one‑click GPU as a Service (GPUaaS) and policy-driven scheduling to maximize compute utilization while controlling costs.
2. AI Development Center provides an integrated development environment (IDE) with data integration, monitoring, automation, dashboards, pipelines, model repository, and CI/CD integration for rapid experimentation and deployment.
3. GenAI App Engine lets you deploy GenAI workloads, expose secure LLM APIs, and iterate on GenAI projects with built‑in access control and monitoring. It supports using custom models or fine-tuning off‑the‑shelf LLMs, with tooling that simplifies data ingestion, vector DB creation, and feedback collection.

The platform is silicon/cloud/vendor-agnostic and aims to help IT teams deliver multi-tenant, scalable AI workflows with predictable ROI.

Core Capabilities

• Unified control plane for on‑prem, cloud, and hybrid GPU resources
• Multi-tenant security with role-based access control and isolated networks/storage
• Dynamic, quota-based resource governance and fractional GPU provisioning
• One‑click GPUaaS and optimized scheduling across clusters
• Comprehensive AI development environment with data integration, monitoring, pipelines, and CI/CD
• Model repository, dashboards, automation, and self-serve compute
• GenAI App Engine for rapid deployment of secure LLM APIs
• Secure networking, authentication, and monitoring for GenAI workloads
• Flexible deployment options for enterprise-scale AI workloads

Feature Highlights

• Multi-tenant GPU resource management across on‑prem, cloud, and hybrid environments
• One‑click GPUaaS with dynamic fractional GPU provisioning
• Quota management and usage-based billing for cost control
• Priority-based, scalable job scheduling across diverse clusters
• Secure isolation of networks and storage per tenant
• Integrated AI development center with IDE, pipelines, and CI/CD
• Comprehensive model repository, monitoring, and dashboards
• GenAI App Engine for secure, scalable LLM deployment with built-in access control
• Silicon, cloud, and vendor agnostic platform to fit existing infrastructure
• End-to-end workflow support from development to production

How It Helps

• Accelerates AI project delivery by consolidating infrastructure, development, and deployment tools
• Improves resource utilization and reduces total cost of ownership through centralized control and scheduling
• Enhances security and compliance with multi-tenant isolation and robust access controls
• Enables rapid GenAI experimentation and production with managed endpoints and monitoring

Suitable For

• Enterprises needing scalable, secure AI infrastructure across multi-cloud and on‑prem environments
• Teams requiring centralized governance, reproducible experiments, and scalable GenAI deployment
• IT and DevOps groups aiming to streamline AI workflows and optimize GPU usage