Galileo AI vs LangSmith (2026)
Updated March 9, 2026
Overview
Galileo is a data intelligence platform for AI that helps teams evaluate, debug, and improve LLM applications. It provides metrics for hallucination detection, context adherence, chunk quality, and response completeness. Galileo's guardrails can be deployed in production to catch quality issues in real-time.
LangSmith is LangChain's platform for tracing, evaluating, and deploying AI agents. Compare its features, pricing, pros and cons, and alternatives.
Key features
Core capabilities each platform advertises.
- LLM output quality evaluation
- Hallucination guardrails
- RAG evaluation metrics
- Data-centric AI debugging
- Automated error detection
- Native tracing for LangChain and LangGraph
- OpenTelemetry and multi-language SDKs
- Offline and online evaluations
- Annotation queues and datasets
- Prompt Hub with versioning
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Generous free tier with 5,000 traces/month including Agent Reliability Platform
- Recognized as Gartner Cool Vendor demonstrating industry validation
- Research-backed metrics providing scientific rigor to evaluations
- Real-time observability with automated drift detection and alerting
- Established team of 142 employees providing solid support capacity
Cons
- Limited public information about advanced features and capabilities
- Pro plan pricing jumps from free to $100/month with potential gaps for small teams
- Less community-driven compared to open-source alternatives like Langfuse
Pros
- Native LangChain and LangGraph tracing with no extra instrumentation
- Evals, datasets, and annotation queues sit in the same workspace as traces
- Tracing, deployment, and sandboxes from one vendor
- Framework-agnostic SDKs and OpenTelemetry support
Cons
- Per-seat pricing on Plus, and the free plan allows one seat
- 14-day base retention, with longer retention billed at a higher rate
- LLM Gateway is still in beta
- Self-hosting and hybrid deployment are Enterprise only
Galileo AI or LangSmith — which should you choose?
Choose Galileo AI if you wantChoose if you want
- Monitoring LLM output quality
- Detecting and preventing hallucinations
- Evaluating RAG pipeline accuracy
- Debugging data quality issues
- Continuous quality assurance
Choose LangSmith if you wantChoose if you want
- Debugging LangChain and LangGraph agents
- Evaluating agent output against datasets
- Human review through annotation queues
- Deploying long-running agents
Compare Galileo AI and LangSmith on your own traffic
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