Galileo

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Introduction

Galileo describes itself as “the AI observability and eval engineering platform where offline evals become production guardrails”. The official site focuses on capturing ground truth, building accurate evals and stopping failures rather than just monitoring them.

It builds datasets from synthetic, development and live production data, captures subject-matter expert annotations, and auto-tunes metrics rather than relying on generic evals. At review time, the Pricing link on galileo.ai redirected to Splunk’s pricing page for Agent Observability, so confirm the current commercial arrangement with the vendor.

Features

1. Datasets: Build from synthetic, development and production data.
2. Expert annotation: Capture SME labels as a living ground truth.
3. Metric tuning: Auto-tunes eval metrics; the site criticises generic evals under 70% F1.
4. Guardrails: Turn offline evals into production guardrails.
5. Tracing: Observe models, prompts, functions, context and MCP server calls.
6. Multi-judge evals: Combine several judges, with cost shown per evaluation.

Pros

1. Eval quality focus: Emphasis on accurate, tuned metrics.
2. Guardrails: Moves from detection to prevention.
3. Enterprise users: Testimonials from Cisco’s Outshift and others; vendor-supplied.
4. Agent support: Traces cover tools and MCP calls.
5. Free start: The site offers “Get Started for Free”.

Cons

1. Pricing unclear: Pricing link redirected to Splunk at review; see site.
2. Proprietary: Not open source.
3. Enterprise orientation: Best value at scale.
4. Annotation effort: Ground truth needs expert time.
5. Judge costs: Multiple judges increase cost per eval.

Usage and Links (Example)

Sign up from galileo.ai, instrument your app with the SDK, log traces, build a dataset from production samples, tune a metric with expert annotations, and promote it to a guardrail. See the docs linked from the site.

Resources:

• Galileo website
• Docs

Pricing

See site. At review time the Pricing link on galileo.ai redirected to Splunk’s pricing page (Agent Observability). A free start is offered.

Recommended for?

1. Enterprises running AI agents in production that need guardrails.
2. Teams with domain experts who can label ground truth.
3. Groups unhappy with generic LLM judges.
4. Not a fit if you need open-source or self-hosted tooling.

Conclusion

Galileo focuses on accurate, tuned evals that become production guardrails for AI apps and agents.

Clarify pricing and ownership with the vendor before committing.