LLM observability & evaluation · Galileo

Galileo

LLM observability and evaluation platform with real-time guardrails, aimed at monitoring agents and generative AI in production.

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Galileo provides tracing, evaluation, and monitoring for LLM and agent applications, with a particular focus on production guardrails that can intervene on live traffic (blocking or flagging hallucinations and unsafe outputs) rather than only reporting on issues after the fact. It supports custom evaluation metrics run at scale, analytics dashboards for spotting quality trends across large trace volumes, and role-based access control for teams. Pricing scales primarily with monthly trace volume: a free tier covers a small trace allowance with unlimited users and custom evals, a Pro tier raises the trace cap with a flat monthly fee, and Enterprise removes the cap with custom rate limits, choice of hosting (hosted, VPC, or on-prem), and real-time guardrails backed by low-latency inference infrastructure.

At a glance

Vendor Galileo
Pricing model Usage-based
Free tier Yes
Deployment Cloud, Self-hosted
Open source No
Best for Teams that want real-time guardrails intervening on production traffic, not just after-the-fact dashboards.

Pricing

Free tier includes a monthly trace allowance with unlimited users and custom evals; Pro is a flat monthly fee for a higher trace cap; Enterprise is custom with unlimited traces and choice of hosting.

Plan Price Notes
Free $0/month 5,000 traces/month, unlimited users, unlimited custom evals
Pro $100/month, billed yearly 50,000 traces/month, standard RBAC, advanced analytics, dedicated Slack support
Enterprise Custom Unlimited traces, custom rate limits, hosted/VPC/on-prem deployment, real-time guardrails, dedicated CSM

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Tracing for LLM and agent applications
  • Real-time production guardrails against hallucinations and unsafe outputs
  • Custom evaluation metrics at scale
  • Analytics dashboards for trend detection across traces
  • Role-based access control
  • Hosted, VPC, or on-prem deployment on Enterprise

Integrations

Profile last reviewed September 21, 2026

Alternatives

Patronus AI Evaluation-focused platform offering pre-built and custom evaluator models to score LLM outputs for accuracy, safety, and quality. Braintrust Evaluation-first platform for testing, scoring, and comparing LLM application changes, with production tracing built in. Arize Phoenix Open-source, local-first tracing and evaluation library for LLM and agent applications, with an optional path to Arize's commercial platform.

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Terms to know

Data quality The degree to which data is accurate, complete, consistent and fit for the purpose it is being used for. Data observability Continuous automated monitoring of pipelines and datasets to catch freshness, volume and quality problems early. Machine learning Building models that learn patterns from data to make predictions or decisions, rather than following hand-coded rules. LLM observability Monitoring a language model's live behavior in production, tracking its inputs, outputs, latency, cost, and failure patterns. Role-based access control (RBAC) Granting data or system permissions based on a user's assigned role rather than configuring access for each person individually.

Related guides

How to choose an LLM observability tool Pick an LLM tool by whether you need tracing, scoring or a gateway first — most teams eventually need all three, rarely from one vendor.