Find the right home
for your AI stack.
Compare tools. Plan your move.
Build with confidence.
Written by Lunary. Built to help you choose.
From the first prompt to the final answer.
Hosting, collaboration, cost, and control.
Your data. Your models. Your next move.
Good tools. Different strengths.
No scorecards with a predetermined winner. Just the decisions worth making before you commit.
LangSmith
Tracing, evaluation & the LangChain ecosystem
Langfuse
Open-source observability & prompt workflows
Helicone
AI gateway & request observability
Start with the work you do.
A useful tool should fit the way you ship. Explore the workflows that matter to your team.
The best agent observability shows why the task failed.
Choose LLM observability for AI agents by tool execution, trace context, retries, task outcomes, and cost per successful task. Compare a practical shortlist.
Explore guide Choosing LLM evaluation toolsChoose an evaluation tool that changes your release decision.
Compare LLM evaluation workflows with a practical rubric for datasets, baseline comparisons, human review, production failures, and prompt testing.
Explore guide Choosing prompt management toolsManage prompts like changes your users will notice.
Compare prompt management tools by versioning, application retrieval, testing, collaboration, and incident reproduction—not just an editor feature list.
Explore guide Lunary for AI engineersGo from a failed run to a fix you can explain.
Use Lunary to inspect model and tool runs, debug customer conversations, test prompt changes, and build an evidence-based AI engineering workflow.
Explore guide Lunary for product teamsUnderstand what customers experience with your AI.
Use conversation context, feedback, and prompt review to help product and engineering teams understand AI failures and measure meaningful improvements.
Explore guide Lunary for platform teamsGive every AI team a trace they can trust.
Build a reliable LLM observability foundation with Lunary: instrumentation standards, OpenTelemetry mapping, data controls, ingestion health, and deployment validation.
Explore guide Lunary + MCPBring Lunary docs into your editor. Trace the tools you build.
Connect the official Lunary Docs MCP server to your editor and learn how to instrument MCP tool execution separately with Lunary SDK or OpenTelemetry.
Explore guideMake your next move a considered one.
Export what matters, preserve your history, and validate the new setup before you switch.
Export LangSmith data without losing the useful context.
Export LangSmith runs with the SDK or eligible bulk export, preserve trace relationships, validate an archive, and prepare selected examples for Lunary.
Explore guide Langfuse export guideExport Langfuse data with a clear audit trail.
Use Langfuse UI, API, or blob-storage exports, reconcile observations and scores, and prepare a controlled migration or evaluation dataset in Lunary.
Explore guide Helicone export guideExport Helicone requests with bodies, sessions, and provenance.
Plan a Helicone export using its documented ETL or REST routes, preserve request bodies and session metadata, and prepare a controlled move to Lunary.
Explore guideYour next release.
A little more certain.
Trace a real workflow. Understand what happened. Make the next version better.