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Galileo

Freemium
genaillmmlopsllmopsai observabilityai evaluationragenterprisedata scienceai safety

Galileo is a powerful, enterprise-focused platform for a critical part of the GenAI stack: evaluation and observability. It is essential for serious, large-scale AI deployment but may be too complex and costly for smaller projects.


Galileo is the GenAI platform for the enterprise, helping teams evaluate, monitor, and guard their LLMs to build and ship trustworthy AI with confidence.

Galileo is a comprehensive software platform designed for enterprise teams building applications with Large Language Models (LLMs). It provides a suite of tools to manage the entire lifecycle of a generative AI product, from experimentation and evaluation to production monitoring and governance. The platform helps data scientists and ML engineers assess the quality of different prompts, models, and retrieval-augmented generation (RAG) systems, identifying issues like hallucinations, data drift, and toxicity before they impact users. Once an application is live, Galileo offers real-time observability to track performance and user interactions, alongside configurable guardrails to prevent harmful or inappropriate outputs. It's built for organizations that need to de-risk their AI investments and ensure their generative AI applications are reliable, secure, and trustworthy. The platform aims to move teams from ad-hoc experimentation to building robust, production-grade AI systems with confidence and control.

Pros

  • Provides a unified platform for the entire GenAI development lifecycle.
  • Strong focus on enterprise-grade reliability, governance, and security.
  • Offers a free 'Community Edition' for individuals and small teams.
  • Supports a wide range of models, vector DBs, and frameworks.
  • Real-time guardrails are critical for deploying safe AI in production.

Cons

  • Enterprise pricing is not public and likely expensive.
  • Can be complex to integrate for teams without MLOps experience.
  • May be overkill for simple or non-critical LLM applications.

Key features

  • LLM evaluation for prompts, models, and embeddings
  • Production monitoring for hallucination, toxicity, and data drift
  • Real-time interception guardrails to block harmful outputs
  • Observability and evaluation for Retrieval-Augmented Generation (RAG)
  • Root cause analysis for model errors and failures
  • Automated data quality checks for unstructured text data
  • Fine-tuning studio for customizing open-source models
  • Metrics for PII detection, topic drift, and security threats

Integrations

OpenAIAnthropicGoogle Vertex AIAWS BedrockAzure OpenAIHugging FaceLangChainLlamaIndexPineconeWeaviateChroma

Target audience

Data scientists, ML engineers, and AI product managers in enterprises building production-grade generative AI applications.


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Key Metrics

Founded

2021

Headquarters

San Francisco, USA

Pricing Tiers

Community

Free

Enterprise

Custom


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