Comet
An AI observability platform for debugging, evaluating, and monitoring LLM applications and agent workflows
- Also known as
- comet
Available worldwide
What is Comet?
A platform that helps developers trace agent execution, evaluate performance with automated metrics, and monitor systems in production. It provides experiment management, dataset handling, and tools to identify and fix agent failures before users encounter them.
Comet pricing
Plans, per-tier features and add-ons, dated and linked to live pricing. Pricing changes often; always verify at source before you rely on it.
Free tier available; open-source self-hosted option under Apache-2.0; enterprise plans available
Free Tier
FreeNo credit card required, generous free tier for individual use
Open Source Self-Hosted
Apache-2.0 licensed, deployable on Kubernetes with Helm
Platform & deployment
Independently observed- Web
- Cloud / SaaS
- Self-hosted
Integrations (4)
Independently observed- LangChain
- OpenAI
- Claude Code
- Codex
Comet alternatives
Other experiment tracking we track, ranked by the same independent score.
- PolyaxonKubernetes orchestration platform for machine learning and AI workload managementlow · 26%
- Guild AIA control plane for managing, monitoring, and governing AI agents across an organizationlow · 20%
- Amazon SageMaker ExperimentsA fully managed machine learning platform for building, training, and deploying models at scale with integrated infrastructure and toolslow · 42%
- ValohaiAn MLOps platform for orchestrating machine learning workflows across experimentation, training, and production environmentslow · 22%
- DVCLiveA Python logging module for machine learning experiment tracking that integrates with version controllow · 3%
Compare Comet
Side by side against other experiment tracking, attribute by attribute, with a source on every value.
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Comet, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Price level | 80 | 0.05 | 4.2 | ✓ |
| Integrations | 51 | 0.04 | 2.1 | ✓ |
| Pricing transparency | 25 | 0.08 | 2.1 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Capabilities | 0 | 0.05 | 0.0 | - |
| Security posture | 5 | 0.07 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 60 | mediumsource · 2026-08-19 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-19 · 75% |
Pricing
Security
| Attribute | Value | Evidence |
|---|---|---|
| Gdpr | Yes | highsource · 2026-08-19 · 75% |