LLM Observability
Adopt AI with confidence
AI is already inside your business, whether you sanctioned it or not. Sumo Logic brings every prompt, every model call, and every AI agent action into one place, so you can see what’s happening across your Claude, ChatGPT, and custom LLM environments so you can say yes to AI adoption and act on issues in real time.
Monitoring Claude and ChatGPT usage
ChatGPT and Codex now sit alongside Claude as everyday tools for research, content, and code. Sumo Logic gives you the detailed metadata, content insights, and audit trails to flag data-sharing behavior that violates policy and identify usage patterns before they become incidents, without adding a new tool to your stack.
Track spend and usage across every model
As teams mature past a single vendor, engineers start routing requests across open-source and proprietary models through proxies like LiteLLM, spend follows. With visibility into these models, you can discover runaway spend while it’s still a line item, not a surprise.
Summary Agent: Providing clear alert context
The Summary Agent automatically explains what triggered an Insight, highlighting key signals and context so analysts can quickly assess scope and prioritize response.
Spend less time sifting through raw logs with clear, actionable summaries ready to share across teams.
Observe the AI you built yourself
Custom AI applications need the same observability standards as the rest of your infrastructure. OpenLLMetry is an open-source framework that extends OpenTelemetry, so your engineering team can pinpoint performance bottlenecks in LLM calls and detect anomalous agent behavior. Custom applications get the same performance and reliability scrutiny as the rest of your stack, on the same platform your team already uses.
Know what your agents are connected to
Agentic AI doesn’t stop at the model. Agents call tools, plugins, and MCP servers that can reach production data on their own. Sumo Logic surfaces MCP server lifecycle events, including creation, deletion, updates, and tool policy changes, and ties every action back to the API key that authorized it, so nothing acts without accountability.
Why Sumo Logic
Visibility built for the AI your business actually runs
Sumo Logic already unifies your telemetry on a single platform. Extending that same visibility to AI means your team doesn’t have to learn a new tool, build a custom pipeline, or choose between enabling AI adoption and staying in control.
Accelerate AI adoption
Scale AI usage with confidence instead of guesswork. Full visibility into how AI is actually used across your organization lets you say yes to more tools, faster.
Reduce risk exposure
Detect sensitive data leaks and unauthorized access with real-time monitoring, out-of-the-box detection rules, and policy enforcement, before a shared prompt becomes a reportable incident.
Meet compliance requirements
Maintain a comprehensive, searchable audit trail with precise accountability for every user and administrative action across every model your organization touches.
Respond faster
Cut investigation time from hours to seconds. Sumo Logic Dojo AI agents give you full context on AI-related incidents, right alongside the rest of your environment to AI quickly triage and resolve incidents.
FAQ
Still have questions?
Coverage depends on the app. Compliance apps like the Claude Compliance App and ChatGPT Compliance App focus on activity logs, metadata, and audit trails rather than full conversation content. Check each app’s documentation in the app catalog for the specific data it collects.
Sumo Logic supports direct integrations with Claude and ChatGPT/Codex through dedicated compliance apps, plus visibility across more than one hundred models through the LiteLLM App and custom LLM applications through the OpenLLMetry App.
No. Each app is available directly in the Sumo Logic App Catalog and is designed to bring AI activity into your existing workflows, dashboards, and retention policies without new tooling.
Yes. The LiteLLM App and OpenLLMetry App are built to surface AI activity that started as engineering experimentation, including model usage that may not have gone through a formal procurement process, so you can bring it into policy rather than discover it during an incident.
Ready to see what your AI is actually doing?
Bring your models, agents, and prompts into one view, and confidently accelerate your AI adoption.
