Galileo
@rungalileo • 1,460 subscribers
The fastest way to ship reliable AI apps - Evaluation, Experimentation, and Observability Platform
Videos
Multi-agent systems offer incredible potential and unprecedented risks. How do you solve for observability, failure mode analysis, and guardrailing in the era of agents? Today, we’re announcing our Agent Reliability platform to observe, evaluate, guardrail, and improve agents at scale. You can get started with the complete platform for trustworthy agentic AI today for free, and here’s how we’re solving some of the biggest challenges in agent reliability: - Observability redesigned for agents Trace views collapse under complex workflows, so we created the Graph View, Timeline View, and Conversation View to offer rich, intuitive visualizations of agent decisions, tool calls, and conversation flows. This multi-dimensional approach enables teams to pinpoint exactly where and why agents deviate or fail. - Automated Failure Mode Analysis with our new Insights Engine Our Insights Engine ingests your logs, metrics, and agent code to automatically surface nuanced failure modes and their root causes. But knowing the problem is not enough; you need to know how to fix it. Insights Engine delivers actionable fixes and can even apply them automatically. With adaptive learning, your insights become smarter and more relevant as your agents evolve. - Evaluating Agents Across Multiple Dimensions Agentic systems interact across complex pathways, and evaluating their performance requires new metrics that reflect this increasing complexity. To deliver comprehensive agentic measurements, we’ve added more out-of-the-box agent metrics like flow adherence, agent flow, agent efficiency, and more. For specialized domains and unique workflows, custom metrics powered by our new Luna-2 small language models can be rapidly designed and fine-tuned for your specific use case. - Real-Time Guardrails Powered by Luna-2 As AI agents become more autonomous and complex, failures like hallucinations or unsafe actions increase dramatically. Without real-time guardrails, these errors will hurt your user experience and brand reputation. Our Luna-2 family of small language models is purpose-built to provide low-latency, cost-effective guardrails that actively stop agent errors before they happen. With support for out-of-the-box and custom metrics, Luna-2 enables enterprises to enforce safety, compliance, and reliability at scale. Enterprises running hundreds of agents and processing hundreds of millions of queries daily already rely on Galileo’s Agent Reliability platform to protect their users, safeguard brand trust, and accelerate innovation. Agent Reliability is available starting today. Try it for free and experience the new standard in AI reliability. Learn more below 👇
Galileo1,276,298 views • 1 year ago
Debugging agents shouldn’t feel like detective work. Today, we’re excited to release two new AI agent interfaces that make agent observability & evaluations even more effective. 🔎 Timeline View – See execution flow and bottlenecks at a glance. No more guessing where your agent gets stuck. 💬 Conversation View – Experience exactly what your users see. Debug from the user's perspective, not just the system's. Combined with last week's Graph View, you now have three complementary ways to debug your agents: → Graph: Visualize decision paths and tool usage → Timeline: Spot performance bottlenecks instantly → Conversation: See the user experience end-to-end AI evaluations + observability are crucial to building reliable AI. These interfaces make it simpler to identify blockers and improve your agents faster. See all three views in action, and try it free with the link below 👇
Galileo, now part of Cisco499,481 views • 1 year ago
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