ClearML

https://clear.ml/

Open-source ML experiment tracking, orchestration, and data management. Allegro AI commercial; widely used in research labs.

At a glance

Type
ML experiment + orchestration
Tier
T2
Created
2018
Latest release
searched not found
License
Apache-2.0 (Core)
Pricing
searched not found
Funding
$30M total raised through Series A 2022 (Atreides Mgmt led); rebranded Allegro AI -> ClearML.

Taxonomy

storage
n/a
retrieval
n/a
persistence
n/a
update
n/a
unit
n/a
governance
n/a
conflict
n/a

When to use

Optimised for: searched not found

Anti-fit: searched not found

Pros & cons

Pros

searched not found

Cons

searched not found

Claims & capabilities

$30M Series A 2022; ~5.5k OSS stars; end-to-end MLOps incl. experiment tracking, orchestration, data management; 2024 added serving + agents.

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
searched not found
Embedding model
not applicable — not a memory product
Multi-tenancy
searched not found
MCP
searched not found
A2A
searched not found
OpenTelemetry
searched not found

Similar systems

Other training infrastructure in the catalog, ranked by inbound references.

  • Azure Machine Learning T1

    Microsoft Azure's managed ML platform — pipelines, AutoML, Designer, prompt flow (LLM). Heavy integration with Azure OpenAI and Azure AI Studio.

  • LoRA T3

    Microsoft Research's Low-Rank Adapters method — trains rank-r matrices added to attention weights; 10000x parameter reduction. Foundation of all adapter-style fine-tuning.

  • DPO T3

    Stanford method that converts RLHF into a supervised-learning loss over preference pairs — no separate reward model needed; widely adopted alignment recipe.

  • GRPO T3

    DeepSeek-Math's GRPO — group-relative advantage estimation replacing PPO's critic. Used in DeepSeek-R1 reasoning post-training; widely adopted in OSS reasoning RLHF.

  • Accelerate (Hugging Face) T1

    Hugging Face's abstraction over distributed-training backends (DDP, FSDP, DeepSpeed, Megatron). Minimal code change to scale a PyTorch script.

  • Argilla T2

    Open-source data-quality platform for LLM training data — human-in-the-loop labelling, RLHF data collection, dataset curation. Acquired by Hugging Face 2024.

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.