Galileo AI
LLM evaluation and observability platform for production AI applications and agents. Galileo provides metrics for hallucination detection, context adherence, completeness, and chunk relevance specifically for RAG pipelines. Includes real-time monitoring of agent production traffic with automatic quality scoring, plus offline evaluation datasets and experiment tracking.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
SOC2 certified. LLM prompts, responses, and retrieved context are logged to Galileo — data handling agreements important. HTTPS enforced. Agent query content is stored on Galileo servers.
⚡ Reliability
Best When
You're running production RAG agent systems and need automatic hallucination monitoring, context adherence scoring, and retrieval quality metrics without building a custom eval framework.
Avoid When
Your agent doesn't use RAG, or you need simple assertion-based testing — Braintrust, PromptFoo, or manual evaluation are simpler and cheaper.
Use Cases
- • Evaluate agent RAG pipeline quality with automatic hallucination and context adherence metrics without writing custom evaluation code
- • Monitor production agent traffic in real-time for quality degradation, hallucination spikes, or prompt injection attempts
- • Run automated evaluation sweeps comparing different agent prompts, retrieval strategies, or LLM models on test datasets
- • Track agent quality metrics over time with dashboards showing hallucination rate, answer relevance, and context utilization trends
- • Detect and debug agent failure modes by drilling into specific low-quality responses with Galileo's diagnostic tools
Not For
- • Teams that only need simple pass/fail unit tests — LangSmith or Braintrust are simpler for basic evaluation workflows
- • Non-RAG LLM applications — Galileo's deepest features are RAG-specific; general LLM evaluation has many cheaper alternatives
- • Teams with very limited budgets — Galileo's pricing is enterprise-oriented
Interface
Authentication
API key passed during SDK initialization (GALILEO_API_KEY environment variable). Keys provisioned in Galileo dashboard. No scope granularity.
Pricing
Free tier is suitable for evaluation experiments. Production monitoring requires paid plan based on logged call volume. Enterprise pricing for high-volume monitoring.
Agent Metadata
Known Gotchas
- ⚠ Evaluation metrics (hallucination, context adherence) are computed by Galileo's internal LLM — there is an additional LLM cost per evaluation call
- ⚠ Metric computation is asynchronous — logged calls don't show metrics immediately; allow 10-60 seconds for scoring to appear in dashboard
- ⚠ RAG-specific metrics require structured logging of query, context chunks, and response — unstructured logging reduces metric quality
- ⚠ Galileo models are trained on Galileo's evaluation benchmark — hallucination scores may not perfectly align with domain-specific definitions
- ⚠ Data retention policies should be reviewed before logging sensitive user queries — all logged data goes to Galileo's servers
- ⚠ SDK instrumentation must be added to agent code — not a zero-code observability solution
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Galileo AI.
Scores are editorial opinions as of 2026-03-06.