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Galileo

Galileo review 2026: enterprise AI evals, observability, guardrails, and Luna evaluator models for RAG and agents — features, pricing, pros, cons.

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In Plain English

Galileo review 2026: enterprise AI evals, observability, guardrails, and Luna evaluator models for RAG and agents — features, pricing, pros, cons.

OverviewFeaturesPricingUse CasesFAQAlternatives

Overview

Galileo (galileo.ai) is an enterprise-focused AI quality platform that targets the full lifecycle of LLM and agent development — pre-launch evaluation, production observability, and runtime guardrails — under one product surface. The platform is built around Luna, Galileo's family of small evaluator models specifically trained to score hallucinations, instruction adherence, context relevance, completeness, and chunk attribution in RAG systems with much lower latency and cost than calling a frontier LLM as judge. Galileo Evaluate lets engineers run scored evals across datasets and surface specific failure modes; Galileo Observe streams production traces with span-level scoring and slicing by tag, user, and version; Galileo Protect provides real-time guardrails that can block or rewrite unsafe responses; and Galileo Agentic Eval gives multi-step tracing and root-cause analysis for agent traces, including identifying which step in a tool-use chain produced the wrong answer. Customers include Twilio, JPMorgan Chase, HP, and other large enterprises that need a single vendor for evaluation, monitoring, and safety on regulated workloads. Pricing is not publicly listed; Galileo offers a developer-tier free trial, paid Pro subscriptions for production workloads, and Enterprise contracts with VPC deployment, custom Luna fine-tuning, and dedicated success management.

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Key Features

  • •Automated hallucination detection using proprietary ChainPoll methodology
  • •Real-time production monitoring for LLM applications with custom alerting
  • •RAG pipeline evaluation covering both retrieval and generation quality
  • •Guardrail Metrics scoring for factuality, toxicity, tone, and relevance without ground-truth labels
  • •Prompt experimentation and A/B testing with side-by-side comparison
  • •Full trace-level observability with drill-down from aggregate metrics to individual requests
  • •Real-time guardrails (Protect module) to block or flag low-quality responses before they reach users
  • •Integration with LangChain, LlamaIndex, OpenAI, Anthropic, and custom model endpoints
  • •Collaborative annotation workflows and shared dashboards with role-based access control
  • •Cost tracking and latency analysis across models and prompt configurations

Pricing Plans

Free Trial

Free

    Pro

    Custom

      Enterprise

      Custom

        See Full Pricing →Free vs Paid →Is it worth it? →

        Ready to get started with Galileo?

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        Best Use Cases

        🎯

        Enterprise RAG quality monitoring with chunk-attribution scoring

        ⚡

        Agent root-cause analysis on multi-step tool chains

        🔧

        Real-time guardrails on customer-facing LLM applications

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        Regulated industries (financial services, telecom, healthcare) needing one quality vendor

        Pros & Cons

        ✓ Pros

        • ✓Luna evaluators are dramatically cheaper than LLM-as-judge — eval coverage can stay on in production
        • ✓End-to-end coverage: evals + traces + guardrails + agent root-cause from one vendor
        • ✓Strong enterprise compliance posture (VPC, audit, SSO) suitable for regulated industries

        ✗ Cons

        • ✗No public pricing — every conversation starts with sales, which slows POC adoption
        • ✗Heavier and more opinionated than open-source [/tools/langfuse](/tools/langfuse) or [/tools/arize-phoenix](/tools/arize-phoenix) — early-stage teams may find it overkill
        • ✗Luna evaluators are proprietary — verify quality on your domain before assuming they replace LLM-judge in your stack

        Frequently Asked Questions

        How much does Galileo cost?+

        Galileo pricing starts at Free. They offer 3 pricing tiers including a free option.

        What are the main features of Galileo?+

        Galileo includes Automated hallucination detection using proprietary ChainPoll methodology, Real-time production monitoring for LLM applications with custom alerting, RAG pipeline evaluation covering both retrieval and generation quality and 7 other features. Galileo review 2026: enterprise AI evals, observability, guardrails, and Luna evaluator models for RAG and agents — features, pricing, pros, cons....

        What are alternatives to Galileo?+

        Popular alternatives to Galileo include braintrust, langfuse, deepeval, helicone. Each offers different features and pricing models.
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        Alternatives to Galileo

        Braintrust

        LLM Observability

        AI observability platform for evals, production tracing, prompt management, and regression detection.

        Langfuse

        LLM Observability

        Langfuse is an open-source LLM observability and engineering platform providing tracing, prompt management, evaluations, and dataset management for production AI applications.

        DeepEval

        Testing & Quality

        Open-source LLM evaluation framework with 50+ research-backed metrics including hallucination detection, tool use correctness, and conversational quality. Pytest-style testing for AI agents with CI/CD integration.

        Helicone

        LLM Observability

        Open-source LLM observability and AI gateway — logs every prompt, response, cost, and latency across 20+ providers with a one-line proxy or async SDK, plus caching, retries, and prompt experiments.

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        Quick Info

        Category

        AI Evaluation

        Website

        www.galileo.ai
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        More about Galileo

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