Add: Comet

[caabernathy]

Name

Comet

Description

Comet provides an end-to-end model evaluation platform for AI developers, with best in class LLM evaluations, experiment tracking, and production monitoring.

Link

https://www.comet.com/

Layer

Model

Components

Experiment Tracking, Model Registry, Monitoring

License

Proprietary

Current Usage

Found mention of it in an AI Tech Stack article and although I don't have first hand knowledge, it looks like it's being used at companies like Zappos, Uber, and Hugging Face.

Key Features

• Debug and evaluate your LLM applications with Opik: Automatically track all your prompt engineering work. Run automated evaluations on your LLM responses to optimize your applications before and after they hit production.
• Track and visualize your model training runs with Experiment Management: Log all your machine learning iteration to a single system of record. Make it easy to reproduce a previous experiment and compare the performances of training runs.
• Monitor ML model performance in production with Comet MPM: Track data drift on your input and output features after your model is deployed to production. Set customized alerts to capture model performance degradation in real time.
• Store and manage your models with Model Registry: Create a centralized repository of all your model versions with immediate access to how they were trained. Promote models to downstream production systems with webhooks.
• Create and version datasets with Artifacts: Know which exact dataset version a model was trained on for auditing and governance purposes. Leverage remote pointers to reference data already stored in the cloud.

Checklist

• [X] Verified the tool is actively maintained
• [X] Checked that the tool isn't already in the database
• [X] Provided accurate license information
• [X] Included working documentation link

Notes

No response

[github-actions[bot]]

Thanks for submitting a new tech stack item! Here's a template for the PR that you or anyone else can submit to add this to techStackData.ts:

{
  Name: '[Your submission name]',
  Description: '[Your description]',
  Link: '[Your link]',
  Layer: '[Selected layer]',
  Components: '[Component categories]',
  License: '[Selected license type]',
},

To submit:

1. Fork the repository
2. Add your entry to the end of the array in src/data/techStackData.ts
3. Create a pull request

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