comet-ml/opik Alternatives

Choose for a Python-native, notebook-friendly tracing/eval platform with tight Arize integration.

AI Observability & Evaluation

Choose for an eval/testing-centric LLM platform if you want a TypeScript stack and managed eval workflows.

The platform for LLM evaluations and AI agent testing

Choose if you want an agent-specific observability platform with a TypeScript stack and hosted option.

Laminar - open-source observability platform purpose-built for AI agents. YC S24.

Choose if you want OpenTelemetry-native LLM/agent tracing and evals without Opik's server dependencies.

Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs.

Choose for a TypeScript/Python LLM observability and eval platform with self-hosting and broad framework integrations.

🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

Choose for feedback-function-driven LLM evaluation and tracking in Python if you do not need a full production dashboard.

Evaluation and Tracking for LLM Experiments and AI Agents

Choose for an OpenTelemetry-based LLM tracing/eval tool under AGPL if you want a self-hosted option.

Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊

Choose for a full Apache-2.0 tracing/eval/simulation/guardrails platform if you want an all-in-one Opik peer.

Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.

Choose for an agent observability/monitoring/eval SDK with self-hosted dashboard if you prefer a Python-first alternative.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

Choose if you need general OpenTelemetry APM/logs/metrics and can forgo LLM-specific evals and prompt management.

SigNoz is an open-source, OpenTelemetry-native observability platform for your team and their AI agents. Get logs, metrics, and traces in one tool with features like APM, distributed tracing, log management, infra monitoring, etc. Combined with SigNoz MCP and a native AI teammate (in SigNoz Cloud) it helps you build more resilient apps.

Choose if you want a Rust gateway-first LLMOps stack with observability/eval; archived, so weigh maintenance risk.

TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.

Choose if you prefer one-line proxy instrumentation over SDK/server deployment.

🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓

Choose if you want a Go, agent-optimization-first platform rather than Opik's Python/LLM-observability core.

Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.

Choose if you already run MLflow for ML lifecycle and want its newer LLM tracing/eval modules.

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

Choose if prompt design/versioning/delivery is your main need and tracing/eval is secondary.

🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.

Choose if you want Python SDK agent monitoring, cost tracking, and benchmarking without a full eval platform.

Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI

Choose if you only need agent eval/continuous-improvement loops, not a full tracing and monitoring platform.

The Continuous-Improvement Stack for Agents. Our environment data and evals power agent improvement and monitoring.

Choose if you only need offline RAG evaluation metrics and can pair it with a separate tracing backend.

Supercharge Your LLM Application Evaluations 🚀

Choose if you want a pytest-style LLM evaluation framework and will bring your own observability stack.

The LLM Evaluation Framework