allegro

allegro is an MLOps product for teams building machine learning systems. Its pitch is that existing code and experiments can become managed tasks with only a couple of added lines. Its website now presents the platform under the ClearML name, as an AI infrastructure platform.

Main features

• Experiment and task management: turns code experiments into trackable, repeatable tasks.
• Workflow orchestration and automation: runs machine learning pipelines at scale.
• Infrastructure control: connects and manages GPU clusters, on-premises, in the cloud or both, with quota management and usage-based billing records.
• AI development environment: a place to build, train and test models.
• GenAI deployment: launches large language models onto an organisation's own clusters.

Who it serves

Enterprise AI builders and IT teams that need to share GPU capacity across projects. Case studies named include DeepMirror, SIL and ELCA.

Key facts

• Security: multi-tenancy and role-based access control
• Deployment: Kubernetes, on-premises and cloud environments