# Galileo AI

AI observability platform for evaluating and monitoring generative AI apps.

- Category: Developer Tools
- Pricing: Contact for pricing
- Tags: Machine Learning, Security
- Website: https://galileo.ai/?via=aigregator
- Aigregator page: https://aigregator.com/tools/galileo-ai
- API: https://x402.aigregator.com/v1/tools/galileo-ai

## Overview
Galileo AI is an observability and evaluation platform for teams building generative AI applications and agents, covering the workflow from pre-release testing through production monitoring. At its core are Luna, a family of proprietary evaluation foundation models fine-tuned for specific tasks such as detecting hallucinations, checking context quality, spotting data leakage, and catching malicious prompts, which the company says allows monitoring of all production traffic at a fraction of the cost of using general-purpose LLMs as judges.

The platform is organized around three stages: evaluation, where teams compare combinations of prompts, models, embedding parameters, and chain nodes to find the best configuration before shipping; monitoring, which tracks live applications for latency, cost, and behavior with traces and alerts; and protection, which applies guardrail policies to catch errors, hallucinations, and security risks in production. Galileo also includes over 20 pre-built evaluation metrics for retrieval-augmented generation and agent use cases, plus tools for building custom evaluators for domain-specific needs.

Galileo is aimed at enterprise AI teams and developers shipping GenAI applications at scale, and is available as SaaS, in a customer's virtual private cloud, or on-premises. The company reports strong enterprise adoption, including several Fortune 50 customers, though the site does not publish detailed pricing or a list of specific third-party integrations.
## Key Features
- Luna evaluation foundation models
- Pre-built RAG and agent evaluation metrics
- Custom evaluator building
- Production monitoring with traces and alerts
- Guardrail policies for hallucination and security risks

## Use Cases
- Evaluating LLM and agent configurations before release
- Monitoring production GenAI traffic for cost and latency
- Detecting hallucinations and data leakage in AI outputs
- Applying guardrails to block malicious prompts

## Who It Is For
- AI development teams in enterprises
- Data scientists and machine learning engineers
- AI safety and security professionals
- Organizations deploying large language models
- Teams requiring scalable and automated AI evaluation

## Pros
- Provides automated and adaptive evaluations that save time
- Supports continuous testing with low-latency metrics
- Enables proactive safety and security protections in production
- Flexible deployment options suited for enterprise needs

## Cons
- Potential complexity for smaller teams or projects
- Requires GPU infrastructure for optimal performance
- Limited information on pricing and specific integrations

## Alternatives
- Arize AI
- LangSmith

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Source: Aigregator — AI tools directory. https://aigregator.com/tools/galileo-ai