Problem

Galileo solves the AI measurement and reliability problem: GenAI teams cannot confidently ship when they lack visibility into whether applications and agents are accurate, safe, useful, or behaving as intended. The conventional alternatives—human review or using large language models as judges—are expensive, slow, and difficult to scale. The pain is especially acute in enterprise deployments, where a single agent failure can expose sensitive data, incur real costs, or damage customer relationships.

The killer use case is making autonomous agents reliable in high-stakes workflows such as customer service, financial operations, and business automation. Galileo targets the economics of continuous production oversight as well as the quality problem: its Luna-2 models are claimed to reduce production-monitoring costs by up to 97% while providing low-latency protection against failures.

Product / Service

Galileo is an enterprise AI observability, evaluation, and guardrail platform. It offers more than 20 out-of-the-box evaluations for RAG systems, agents, safety, and security, lets teams create custom evaluators that encode domain expertise, and exposes agent behavior across individual steps, tool calls, and outputs. Its central workflow connects development-time testing to production governance, so evaluations can become runtime guardrail rules rather than remaining isolated reports.

The platform uses Galileo’s Luna evaluation models—purpose-built, compact models that approximate expensive LLM-as-judge evaluations—to score quality quickly and cheaply in production. Teams can observe, evaluate, guardrail, and improve agent behavior through a single system, with deployment available through fully managed SaaS, private VPC, or on-premises environments. The benefit is a more continuous, automated reliability layer with lower evaluation cost, faster feedback, and stronger controls for sensitive enterprise workloads.

Market

Galileo competes in the emerging enterprise AI evaluation, LLM observability, and agent-reliability market. Its comparison set includes LangSmith, Arize, Langfuse, Braintrust, and Helicone. Galileo’s positioning is broader than passive trace logging: it combines observability with packaged and custom evaluations and runtime guardrails, aiming to close the loop from testing to production control.

It is not pre-revenue. In its October 2024 Series B announcement, Galileo reported $45 million of new funding and $68 million in total funding, 834% revenue growth since the beginning of 2024, a quadrupling of enterprise customers, and six Fortune 50 customers including Comcast and Twilio. The company also identified HP, Twilio, and Comcast among its customers and said its platform was used by teams ranging from startups to Fortune 50 companies, providing meaningful early enterprise traction even though the evidence does not provide a later quantified revenue or customer update through August 2026.