Comet
FreemiumOpik observability, evaluation, and auto-fix for AI agents with cost intelligence
By Tanmay Verma, Founder · Last verified 05 Jul 2026
6.0k views
Added 4/3/2026
95/100Safe BetIn short
Comet — Opik observability, evaluation, and auto-fix for AI agents with cost intelligence. Best for AI teams shipping production agents needing deep trace observability and automated debugging, Engineering managers tracking and optimizing coding agent spend (Claude Code, Codex), ML teams combining LLM evaluation with experiment management and model versioning. Free to start; paid plans from $179/mo.
Is Comet actually worth it?
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Editorial Verdict
Best for
AI teams shipping production agents needing deep trace observability and automated debuggingEngineering managers tracking and optimizing coding agent spend (Claude Code, Codex)ML teams combining LLM evaluation with experiment management and model versioningEnterprises requiring self-hosted, secure LLM observability with test suitesDevelopers iterating on multi-step agents with continuous improvement via Ollie
Not ideal for
Non-technical users seeking no-code LLM evaluation dashboardsTeams needing only a simple prompt playground without trace-level debuggingProjects with very low agent complexity where basic logging sufficesOrganizations that cannot integrate git-based code automation into their workflow
Best for engineering teams needing deep trace observability plus automated code fixes via Ollie. The cost intelligence for Claude Code and Codex, combined with Test Suites, makes it a strong choice for production agent workflows. Skip if you only need simple prompt playgrounds or no-code evaluation.
Skip Comet if Skip Comet if you only need a basic prompt playground or no-code evaluation — consider Langfuse or Helix instead.
Compare with: Comet vs Phoenix, Comet vs Arize Phoenix, Comet vs Dash0
Last verified: July 2026
What's new in Comet
Checked 2 days agoAcross the latest 10 updates: 5 feature updates, 3 launches and 2 news mentions.
FeatureBlog·6 days agoNewest
How Evaluation-Driven Development (EDD) Works
Turn every AI agent change into a measured experiment to detect regressions and measure performance.
FeatureBlog·8 days ago
Opik + Oracle Agent Specification: Build Once, Run Anywhere
Opik integrates with Oracle's Open Agent Specification for building, testing, and deploying agents.
FeatureBlog·13 days ago
Advanced Claude Code Cost Tracking: How to Save 30% on Token Spend
Techniques to reduce token spend by 30% with Claude Code cost tracking.
LaunchBlog·13 days ago
AI Evaluation Simplified: Automate Dataset & Metric Eval Workflows with Test Suites
Automate dataset and metric evaluation workflows using test suites for AI agents.
NewsBlog·21 days ago
Understanding Your Claude Code Spend: What’s Actually Driving the Cost
Analyzes cost drivers in Claude Code usage to help teams optimize spending.
FeatureBlog·Jun 3
Agent Tracing and Observability: Log & Debug Complex AI Systems
Introduces agent tracing and observability features for debugging complex AI systems.
NewsBlog·May 27
The Best AI Observability Tools for Agentic Systems in 2026
Survey of AI observability tools for agentic systems, highlighting Opik's role.
FeatureBlog·May 15
LLM Cost Tracking Solution: How to Monitor and Control AI Spend in Agentic Systems
Monitors and controls AI spend in agentic systems with LLM cost tracking.
LaunchBlog·Apr 23
Introducing the Opik Agent Playground
Launch of Opik Agent Playground for early-stage agent development and testing.
LaunchBlog·Apr 22
Introducing Ollie: Auto-Fix Your Agent’s Codebase
Ollie auto-fixes agent codebases, enabling repeatable development workflows.
Viability Score
95/100
Safe BetHow likely is Comet to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
momentum
100
funding runway
80
website health
90
wrapper dependency
100
Last calculated: July 2026
How we score →Key Features
- Full trace logging for every agent step
- 30+ LLM-as-a-judge metrics including hallucination detection
- Test Suites for simplified pass/fail evaluation
- Ollie auto-fix coding agent that writes fixes to git
- Opik Agent Playground for rapid agent prototyping
- Cost intelligence for Claude Code and Codex spend
- Human annotation and debugging of individual traces
- Production monitoring for agents
- Experiment management with custom visualizations
- Model versioning and dataset management
- @track decorator for easy integration with any LLM framework
- Self-hosted or cloud deployment
- Real-time trace streaming and visualization
- Supports OpenAI, LangChain, LlamaIndex, Claude Code, Codex
- Integration with PyTorch, TensorFlow, Hugging Face, and more
About Comet
FreemiumAdvancedAPI availableWeb · API · CLI · Desktop
Comet is an AI developer platform that helps teams ship production-ready agents by connecting deep observability directly to action. Its open-source LLM evaluation tool, Opik, enables full trace logging for every agent step, from context retrieval to tool selection. With 30+ built-in LLM-as-a-judge metrics including hallucination detection, and Test Suites for simplified pass/fail evaluation, teams can auto-score traces at scale. The built-in coding agent Ollie analyzes trace and test outcomes, generates fixes, and writes them directly to the codebase under version control. Comet also covers experiment management, model versioning, production monitoring, and cost intelligence for Claude Code and Codex usage. Trusted by over 150,000 developers, Comet is particularly strong for teams that need deep trace-level observability plus automated debugging — a combination few competitors offer. The April 2026 launch of Opik Agent Playground enables rapid prototyping of agent architectures before full instrumentation.
Behind the Verdict
Comet's Opik stands out for its tight loop between observability and action — Ollie auto-fixes are a genuine differentiator. For teams debugging multi-step agents in production, being able to trace every LLM call, annotate failures, and have an agent push code fixes to git is unusually concrete. The cost intelligence for Claude Code and Codex is timely for engineering managers watching coding agent spend balloon. On the flip side, Opik's power comes with a learning curve; non-technical users may find the @track decorator and integration setup daunting. Compared to rivals like LangSmith or Weights & Biases, Comet offers more agent-specific automation (Ollie) and Claude Code cost tracking, but its MLOps heritage (experiment management, model versioning) may feel legacy to teams focused purely on GenAI. The Agent Playground (launched April 2026) helps close the prototyping gap, but it's new. In practice, we'd reach for Comet when we need to obsess over one agent's behavior and auto-fix recurring issues. Where it bites: if your team can't adopt git-based auto-fixes or needs a non-technical dashboard for execs, Opik may feel too developer-centric. Pricing at $179/mo for Teams is fair versus enterprise-tier alternatives, but small teams may chafe at the jump from Free to Teams without a mid-tier option.
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Real-world workflow fit
Concrete scenarios for the personas Comet actually fits — and what changes day-one when you adopt it.
AI engineer building a RAG agent
Integrate @track decorator into your agent code, log traces, and use Test Suites to evaluate context relevance and hallucination.
Outcome: Automated pass/fail reports highlight failing traces; Ollie suggests and auto-commits fixes, reducing debugging time by 50%.
Engineering manager tracking coding agent costs
Use Cost Intelligence to monitor Claude Code and Codex spend per team member, identify wasteful token usage.
Outcome: Cut monthly LLM spend by 20% by optimizing model selection and context strategies.
ML engineer experimenting with new prompts
Use Agent Playground to prototype agent architecture without full instrumentation, then graduate to Opik tracing.
Outcome: Rapid iteration on prompt templates before committing to code; reduce time-to-production by 30%.
Use Cases
- Debugging complex LLM agents with full trace visibility
- Automated testing of agent responses with Test Suites
- Iterative development with Ollie AI-assisted code fixes
- Sandbox testing of agent versions before production
- Monitoring production agent behavior, costs, and governance
- Analyzing Claude Code and Codex spend across your engineering team
- Evaluating multimodal LLMs using product images and metadata
Models Under the Hood
OpenAILangChainLlamaIndexClaude CodeCodexPyTorchTensorFlowHugging Face
as of 2026-07-06
Limitations
- Opik is designed for LLM agent observability and evaluation; it does not provide general ML experiment tracking outside of agent contexts.
- The Ollie auto-fix agent may not always generate correct fixes and requires human review.
- Self-hosting the open-source version may require engineering effort.
as of 2026-06-29
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Comet tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Individual developers or small teams exploring LLM observability with up to 100 experiments
What this tier adds
Free tier includes unlimited OSS Opik self-hosting and limited Cloud Opik traces; community support.
Teams
$179/mo
Ideal for
Growing teams needing full Opik cloud access with unlimited traces and Ollie auto-fix
What this tier adds
Adds unlimited traces, advanced evaluation metrics, Ollie auto-fix, Cost Intelligence, and priority support over Free.
Enterprise
Custom
Ideal for
Large organizations requiring self-hosted deployment, SSO, audit logs, and dedicated support
What this tier adds
Custom pricing includes self-hosted/VPC deployment, audit logs, SSO, custom integrations, and SLA.
Integrations
OpenAILangChainLlamaIndexClaude CodeCodexPyTorchPyTorch LightningHugging FaceKerasTensorFlowGitHubRaySpark NLPVertex AISageMaker
Where the pricing makes sense
The company stage and team size where Comet's pricing actually pencils out — and where peers do it cheaper.
Comet's free tier is generous for small teams — up to 100 experiments. The Teams plan at $179/mo is competitive with Langfuse and Helix, but cheaper than Datadog's observability offerings. Enterprise custom pricing suits large orgs needing self-hosted or VPC deployment.
Setup time & first value
How long it actually takes to get something useful out of Comet — broken out by persona, not the marketing-page minute.
For a developer familiar with Python, getting Opik running with @track decorator takes about 10 minutes. The Agent Playground for prototyping is instant. Teams needing self-hosted deployment (Docker/K8s) should budget a few hours for setup.
Switching to or from Comet
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Migrating in
- →From Langfuse: Import your existing traces via their API and map to Opik's trace model — Comet offers migration scripts.
- →From Helix: Export evaluation results as JSON and import into Opik's experiment management — manual but straightforward.
Migrating out
- ↗To Langfuse: Export Opik traces via its REST API and reingest into Langfuse — no automated tool available.
- ↗To Helix: Use Opik's API to pull evaluation data and upload to Helix — requires custom scripting.
Resources & Guides
Frequently Asked Questions
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Common stack mates teams adopt alongside Comet, with the specific reason each pairing earns its keep.
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