Galileo

Galileo is a GenAI and agentic-application platform that combines evaluation, observability, experimentation, and runtime guardrails. It fits engineering, product, and subject-matter teams responsible for reliable AI behavior, especially those using its supported frameworks and SDKs. The main trade-off is between its unusually broad control surface and practical limits around traces, annual billing, and where SSO can run.

Overview

Galileo brings testing and production oversight into one workflow. Its behavioral analysis looks for agent failure modes and recurring patterns, then helps teams identify potential fixes. Evaluation scores can also influence agent actions, tool permissions, and escalation routes, turning quality and safety checks into operational controls rather than static reports.

Teams can connect through Python or TypeScript SDKs or the API. Documented integrations cover CrewAI, Google ADK, LangChain and LangGraph, OpenAI, Microsoft Agent Framework, Strands Agents, and Vercel AI SDK. Galileo was founded in 2021.

Key features

Evaluation and experiments

Built-in evaluators cover retrieval-augmented generation, agents, safety, and security, while custom evaluators handle application-specific criteria. Experiments provide a structured way to compare datasets, prompts, and runs. Prompt versioning, custom metrics, LLM-as-a-judge scoring, safety evaluations, human review workflows, and CI/CD integration make the platform useful across development, release review, and regression checks.

Observability and guardrails

Observability focuses on agent behavior, failure patterns, and actionable diagnosis. The guardrail workflow can use scores to decide whether an agent proceeds, receives tool access, or escalates. That connection is valuable for teams that need controls during execution, although it requires enough trace capacity to represent real traffic.

Access and deployment

Role-based access control is provided, with groups reserved for paid customers. Deployment choices include Galileo SaaS, Virtual Private Cloud, and on-premises installations. OIDC and SAML single sign-on work only on a customer's own Galileo cluster; SSO is not included with the free version or the hosted app.galileo.ai service. This distinction matters for organizations whose identity policy requires SSO in a hosted environment.

Pricing

Free

The Free plan has no listed price and includes 5,000 traces per month, unlimited users, and unlimited custom evaluations. It is a sensible way to build an evaluation workflow or pilot observability without a seat ceiling, but the monthly trace cap can constrain busy applications and it does not provide the paid access and support features.

Pro

Pro costs $100 a month, billed yearly. It raises the allowance to 50,000 traces per month and adds standard RBAC, advanced analytics and insights, and dedicated Slack support. Pricing scales with the number of traces, so teams should size expected usage rather than treating the headline amount as a fixed ceiling. Pro suits growing teams that need richer analysis and support but can operate within hosted-plan constraints.

Enterprise

Enterprise uses custom billing and removes the standard trace ceiling with unlimited traces and custom rate limits. It adds hosted, VPC, or on-premises deployment; enterprise-grade RBAC and SSO; a dedicated customer success manager; real-time guardrails; 24/7 support by Slack, email, or phone; low-latency dedicated inference servers; and forward deploy. It is the appropriate tier for regulated or high-volume deployments that require infrastructure and support commitments beyond Pro.

Platforms

Galileo is offered through an API, self-hosted deployments, and the web. The deployment menu spans SaaS, Virtual Private Cloud, and on-premises options, while SDK access is available for Python and TypeScript.

Who it's for

Galileo is aimed at engineers, product managers, and subject-matter experts building safe, dependable AI applications. It is particularly well suited to teams that want evaluation results to drive agent behavior and that need one system for experiments, traces, review, and guardrails. Small projects with light traffic may find the Pro commitment and trace model more than they need.

Pros and cons

Pros

• Evaluation connected to runtime controls: Scores can govern tool access, actions, and escalation instead of remaining isolated test output.
• Broad evaluation coverage: RAG, agent, safety, and security evaluators are available alongside custom metrics, human review, and LLM-as-a-judge options.
• Flexible deployment: SaaS, VPC, and on-premises choices support different security and operational requirements.
• Framework reach: Integrations include major agent and model ecosystems, with Python, TypeScript, and API interfaces.

Cons

• Free trace ceiling: 5,000 traces per month limits the free tier for substantial production traffic.
• Annual Pro term: The 100.00 USD monthly price is billed yearly, and the amount scales with trace volume.
• Hosted SSO restriction: OIDC and SAML SSO require the customer's own Galileo cluster, excluding the free tier and hosted app service.
• Some collaboration features are paid: Groups and stronger support arrangements begin above the free plan.

Alternatives

Promptfoo is a better fit when you want a freemium, locally runnable evaluation tool with 10k red-team probes per month, broad provider integrations, and support across desktop, server, API, and web environments.

DeepEval suits teams seeking a free, Apache 2.0-licensed open-source framework that runs locally and in CI/CD.

Giskard is worth choosing for an open-source library with local deployment and basic LLM vulnerability and RAG evaluation reports.

Confident AI fits smaller projects that prefer a freemium service with a two-seat, one-project free tier and capped weekly test runs.

garak is a free open-source option for teams wanting a focused tool without paid plans.

HELM is appropriate when an open-source Python framework with no paid plans is the priority.

Maxim AI is an alternative for teams wanting a freemium platform with a free developer tier, limited seats, workspace, logs, retention, and email support.

For broader category browsing, see LLM Evaluation Tools, Machine Learning Model Monitoring Software, AI LLM Evaluation Tools, AI LLM Observability Tools, LLM Observability Tools, and Model Monitoring Software.

Verdict

Choose Galileo if your team needs evaluations, agent observability, experiments, and guardrails in a single system, particularly with a supported framework and a deployment requirement that may extend to VPC or on-premises. Look elsewhere if you need a fully local open-source workflow, a month-to-month entry plan, or SSO directly on the hosted service.