COMET-ML

Comet ML experiment tracking + Opik LLM observability.

Definition

Comet ML products: (1) Comet ML Experiments: ML training runs tracking similar W&B (hyperparameters + metrics + system metrics + artifacts), comet_ml.Experiment Python SDK, integration TensorFlow + PyTorch + scikit-learn + XGBoost + LightGBM + Keras + HuggingFace Transformers, etc. (2) Comet ML Model Registry: model versions + stages + lifecycle management. (3) Comet ML Workspaces: team + project collaboration. (4) Comet Artifacts: versioned datasets + models + arbitrary files lineage. (5) Comet Reports: embed Markdown + experiment plots collaborative reports. (6) Comet Production: Predictions monitoring + drift detection + alerting deployed models. (7) Opik (Open-source MIT, launched 2024): LLM observability + evaluation platform, traces LLM calls + evaluations + datasets, similar Phoenix Arize + LangSmith + Weave competitor, deepens LLM workflow support Comet ecosystem. Customers: Etsy + Booking.com + Citi + Affirm + Uber + Boeing. Funding: Series A $13M 2020 + Series B $50M 2021 (Yardi Capital lead).

Origin

Comet ML founded 2017 in New York by Gideon Mendels (ex-Google) + Nimrod Lahav + Dor Moshe ; Series A $13M 2020 + Series B $50M 2021 ; Opik launched 2024 OSS MIT.

Example in context

Booking.com data science teams use Comet ML to track ~10000+ ML experiments per year: recommendation models + pricing optimization + search ranking + ETA prediction, Comet integration PyTorch + scikit-learn + LightGBM, model registry production deployment, Opik LLM observability emerging adoption customer service AI agents.

Related terms

• W&B — main competitor.