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Comet

End-to-end AI evaluation platform for tracing, testing, and optimizing LLM applications and autonomous agents at any scale.

Our take: Comet provides a comprehensive suite for AI development, combining Opik's LLM observability with MLOps' experiment tracking.

Best forAI engineers and startup founders who need full visibility into how their LLM apps and agents behave, with automated evaluation to catch regressions before they reach users
ReviewedPricing: Freemium
8.0 out of 105 criteria · see breakdown
Try CometFree tier; Pro at $19/mo
The bottom line

Comet is a versatile and cost-effective solution for AI development, suitable for both small teams and large enterprises.

Our score

Reviewed by the Conversion Gems editorial team. Hover a facet to focus it; click to pin.Tap a facet to focus it.

Community ratings

Shown for context only. Our score is independent.

G2
4.7 out of 5
5+ reviews
Trustpilot
1.5 out of 5
180+ reviews

1.6 / 5 aggregate · across 2 sources

Third-party ratings shown verbatim; aggregate weighted by review volume.

What it is, and why we rate it

One line each. Open a row for detail.

What it really isComet — an AI developer platform offering Opik for LLM observability and evaluation, and MLOps for experiment tracking.
Our takeComet provides a comprehensive suite for AI development, combining Opik's LLM observability with MLOps' experiment tracking.
The platform offers flexible pricing, including a generous free tier and an open-source option for self-hosting, making it accessible for teams of various sizes. Notably, Comet's pricing model is more affordable than some competitors, with the Pro tier at $19 per month, offering expanded usage for growing teams.

Best / not good for

Best for
  • AI engineers
  • Data scientists
  • ML researchers
Not good for
  • Non-technical users
  • Teams requiring extensive customer support
  • Organizations needing highly specialized AI tools
Trade-offs

Friction report

Trade-offs to know before signing up.

  1. Time to value
    Fast: Quick setup with immediate access to core features.
  2. Scale breakpoint
    Pro plan limits at 10 users; larger teams require Enterprise plan.
  3. Walled garden
    Low: Open-source option allows for customization and integration.
Still a fit?
If none of these block you, start on the free plan.
Try Comet

Frequently Asked Questions

Does Comet have a free plan?

Yes. Comet offers both a free managed cloud tier (no credit card required, supports up to 10 team members with a monthly span limit and 60-day retention) and a fully open-source self-hosted version of Opik with no usage caps.

What is the difference between Comet and Opik?

Opik is Comet's open-source product focused on LLM tracing, evaluation, and production observability. Comet as a whole also includes a traditional MLOps platform for experiment tracking, model versioning, and hyperparameter optimization — Opik is the LLM/agent layer on top of that foundation.

What AI frameworks and tools does Comet integrate with?

Comet integrates with LangChain, LlamaIndex, OpenAI, Vertex AI, PyTorch, TensorFlow, Keras, and Scikit-learn, among others. Any custom LLM implementation can also be connected through its SDK.

How quickly can a developer get started?

Onboarding is designed to take minutes — developers add a few lines of code to their existing workflow using Comet's SDK and traces start appearing in the dashboard immediately. Advanced evaluation pipelines and custom metrics take longer to configure but are well-documented.

Is Comet suitable for solo founders or only larger engineering teams?

Comet works well for solo founders and small teams on the free tier, scaling up through paid plans as team size and usage grow. The open-source self-hosted path is also popular among early-stage startups looking to avoid vendor lock-in while still getting full observability.

Alternatives

  • Step up

    Enterprise plan for larger teams and advanced features.

  • Lighter alternative

    Open-source self-hosted version for full control.

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Tags

#llm-evaluation#ai-observability#experiment-tracking

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