Start here for the decision-making essentials: what Comet does, who it is for, how it is accessed, and the first-party sources behind this profile.
PricingCurrent signal
See official pricing
Platforms
Web
API accessNot public
FoundedNot disclosed by source
AvailabilityWeb / remote
LicenseOpik is open source with the full featureset available in the free open-source version
Best suited to
Source-backed fit
Developers building and debugging LLM applications and agents Data scientists and ML practitioners in enterprise environments Engineering teams evaluating chatbots, RAG pipelines, and multi-step agents Teams needing infrastructure-agnostic production model monitoring Organizations requiring self-hosted AI observability on Docker or Kubernetes
AI infrastructure · Tool
Comet
Decision-ready
Comet is the creator of Opik, an end-to-end AI observability platform for developers with best-in-class agent testing, optimization, and monitoring.
Short answers to the questions buyers and builders commonly ask about Comet. Each answer cites the shared ledger below, where every source is listed once.
01What does Comet say it can do?
Opik is an end-to-end AI observability platform for developers with agent testing, optimiz · Tracing provides LLM observability to visualize context retrieval, tool selection, user fe · Diagnostics automatically surfaces, groups, and identifies root causes of recurring issues · Test Suites and Evals provide scoring of traces with 40+ LLM-as-a-judge metrics
Comet is the creator of Opik, an end-to-end AI observability platform for developers with best-in-class agent testing, optimization, and monitoring.
Developers, data scientists, ML practitioners, and engineers in demanding enterprise envir · Over 150,000 developers and AI teams use Opik across startups, research labs, and global e
Comet's end-to-end evaluation platform is trusted by innovative data scientists, ML practitioners, and engineers in the most demanding enterprise environments.
Building, evaluating, and monitoring chatbots, RAG pipelines, and multi-step agents · Manage the complete ML lifecycle in one platform
Whether you're building a chatbot, a RAG pipeline, or a multi-step agent, Opik gives you the tools to go from "it works on my laptop" to "it works reliably in production."
ask_ollie and run_experiment tools are available on Comet Cloud only and fail at dispatch · Cursor enforces a 60-second hard tool-call timeout that does not reset on progress notific
ask_ollie and run_experiment are available on Comet Cloud only — on self-hosted those calls fail at dispatch
Works with OpenAI, Anthropic, LangChain, and 50+ other providers and frameworks · Tracing supports 60+ integrations for instrumenting LLM apps and agents · MCP server integration for AI coding assistants: Claude Code, Cursor, and VS Code Copilot · Supports Python, TypeScript, Java, .NET, Ruby, No-Code, and Multi-Language frameworks
Works with OpenAI, Anthropic, LangChain, and 50+ other providers and frameworks.
Can be self-deployed on local Docker or Kubernetes for full control over data · Build using any infrastructure and serving tools (infrastructure-agnostic) · Available as Opik Cloud (hosted) and as self-hosted (local or Kubernetes) · Self-hosted deployment supported locally and on Kubernetes
Deploy on your own infrastructure with Docker locally or Kubernetes at scale. Full control over your data.
This profile connects the jobs Comet is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Common use cases
Building, evaluating, and monitoring chatbots, RAG pipelines, and multi-step agents
Tracing every LLM call, tool invocation, and agent step for full inspection
Running evaluations with 40+ LLM-as-a-judge metrics on golden datasets
Automatically surfacing and grouping root causes of recurring issues via Diagnostics
Optimizing prompts across agent steps with six optimization algorithms
Tracking production model performance and data drift without ground-truth labels
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
Official website
HTTP 200 verified twice
First-party description
Home
Source-supported facts
Opik is an end-to-end AI observability platform for developers · Tracing provides LLM observability across context retrieval, tool selection, and user feed · Diagnostics detects, groups, and identifies root causes of recurring issues
Capability
Opik is an end-to-end AI observability platform for developers with agent testing, optimization, and monitoring
Capability
Tracing provides LLM observability to visualize context retrieval, tool selection, user feedback scores, and more
Capability
Diagnostics automatically surfaces, groups, and identifies root causes of recurring issues across traces
Capability
Test Suites and Evals provide scoring of traces with 40+ LLM-as-a-judge metrics
Capability
Opik records every LLM call, tool invocation, and agent step so the full chain of events can be inspected
View 32 more verified facts
Capability
Prompt optimization with six optimization algorithms for every step in an agent
Use case
Building, evaluating, and monitoring chatbots, RAG pipelines, and multi-step agents
Audience
Developers, data scientists, ML practitioners, and engineers in demanding enterprise environments
Audience
Over 150,000 developers and AI teams use Opik across startups, research labs, and global enterprises
Practical capabilities
What it helps with
8 documented areas
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Use case
Building, evaluating, and monitoring chatbots, RAG pipelines, and multi-step agents
Use case
Tracing every LLM call, tool invocation, and agent step for full inspection
Use case
Running evaluations with 40+ LLM-as-a-judge metrics on golden datasets
Use case
Automatically surfacing and grouping root causes of recurring issues via Diagnostics
Use case
Optimizing prompts across agent steps with six optimization algorithms
Use case
Tracking production model performance and data drift without ground-truth labels
Use case
Defining custom metrics and triggering real-time production alerts
Use case
Connecting AI coding assistants to traces via the Opik MCP server
Availability
Where it runs and where to get it
Source checked
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
Cost / license
See official pricingOpik is open source with the full featureset available in the free open-source versionOpik is an open-source platform for LLM evaluation and observabilityOpik is an open-source platform for LLM observability and agent optimizationOpik is truly open source, with the full AI engineering feature set available across cloudOpik is Comet's open-source platformOpen source (Opik is open source with full AI engineering feature set)Additional integrations can be requested via the project's GitHub repositoryOpik is an open-source platform for LLM observability and evaluation, with cloud and enter
DeploymentCan be self-deployed on local Docker or Kubernetes for full control over data · Build using any infrastructure and serving tools (infrastructure-agnostic) · Available as Opik Cloud (hosted) and as self-hosted (local or Kubernetes) · Self-hosted deployment supported locally and on Kubernetes
LicenseOpik is an open-source platform for LLM observability and evaluation, with cloud and enter
Model supportNot disclosed by source
Data controlHosted MCP server uses browser-based OAuth authentication with no API key stored in client
Learning curveIntermediate
Primary use casesBuilding, evaluating, and monitoring chatbots, RAG pipelines, and multi-step agents, Tracing every LLM call, tool invocation, and agent step for full inspection, Running evaluations with 40+ LLM-as-a-judge metrics on golden datasets, Automatically surfacing and grouping root causes of recurring issues via Diagnostics, Optimizing prompts across agent steps with six optimization algorithms, Tracking production model performance and data drift without ground-truth labels, Defining custom metrics and triggering real-time production alerts, Connecting AI coding assistants to traces via the Opik MCP server, Manage the complete ML lifecycle in one platform
What to verify before adopting
ask_ollie and run_experiment tools are available on Comet Cloud only and fail at dispatch
Cursor enforces a 60-second hard tool-call timeout that does not reset on progress notific
Evolution and major updates
Comet timeline
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
32 dated updates
Latest first · exact dates
Showing the newest updates and meaningful milestones. Open an entry for its summary and source.
Release note
AWS Brings Third-Party Apps to SageMaker AI Platform
Open details
AWS expanded its SageMaker AI platform with third-party apps, a market development relevant to Comet's distribution channel as a SageMaker Partner AI App.
Comet launches Opik, an open-source LLM evaluation platform
Open details
Comet released Opik as an open-source platform for LLM evaluation, providing tracing, evaluation, and monitoring workflows for generative AI applications.
Comet Introduces Kangas, an Open Source Data Exploration and Model Debugging Tool
Open details
Comet released Kangas, an open-source tool for smart data exploration, analysis, and model debugging in machine learning workflows.
Citation ledger
Recorded sources
17 unique pages
Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
These tools share a workflow, capability or audience with Comet. They may complement it rather than replace it, and are not presented as integrations or endorsements.
AI infrastructure · ToolBraintrustBraintrust is an enterprise-grade AI observability and evaluation platform for tracing production LLM applications, running experiments on datasets, comparing prompts and models, and catching regressions via online scoring and quality gates.Also mapped to AI infrastructure
AI infrastructure · ToolCerebriumCerebrium is a serverless AI infrastructure platform for real-time, high-performance applications. It provides global, region-aware GPU deployment, sub-second cold starts, instant autoscaling, and hardened gVisor workload isolation, with support for voice agents, video models, LLMs, multimodal pipelines, and large-scale batch jobs.Also mapped to AI infrastructure
AI infrastructure · ToolChromaChroma is an open-source (Apache 2.0) data infrastructure for AI that stores embeddings and supports dense, sparse, hybrid, keyword, and regex search across text, images, and audio. It runs as self-hosted single-node, distributed, or managed Chroma Cloud, with AWS CloudFormation deployment, a CLI, and Mem0 integration.Also mapped to AI infrastructure
AI infrastructure · ToolChronosphereFind and fix customer-impacting issues faster and stop paying for data you don’t use. Chronosphere is the world’s most reliable observability platform for microservices and containers.Also mapped to AI infrastructure
