
Observe announced the availability of two new AI agents, AI SRE and o11y.ai, built on its open data lake architecture and knowledge graph.
The new agents drive engineering productivity with intelligent incident investigation and remediation, and faster delivery of production-ready code.
Key Highlights
- Early customers report incident triage up to 10x faster
- Mean time to resolution (MTTR) reduced from hours to minutes
- Observability costs reduced by up to 60%
"As AI code generation accelerates software delivery, the bottleneck has shifted to running and maintaining systems reliably at scale," said Jeremy Burton, CEO of Observe Inc. "AI SRE and o11y.ai directly address these pain points by making systems observable, reliable, and affordable from day one."
The AI SRE agent autonomously applies context, pinpoints root causes, and suggests fixes, so teams can troubleshoot faster at scale.
AI SRE automates incident investigation with a contextual understanding of logs, metrics, and traces in real time. It reduces operational toil, minimizes on-call load, and increases accuracy in root cause identification. Built on Observe's low-cost, scalable data lake architecture, it enables enterprises to have longer data retention, while reducing observability spend by up to 60%. Governance and compliance are built-in with role-based access controls, SOC 2 Type II, ISO 27001, and GDPR support.
AI SRE enables enterprise customization and extensibility through a Model Context Protocol (MCP) Server which integrates natively with Claude Code, OpenAI Codex, Augment Code, Windsurf, n8n and other AI tools. The MCP Server uses Observe's knowledge graph to help agents quickly gather more context from the massive volume of observability data in the data lake, resulting in greater accuracy. Teams can integrate proprietary data, add custom context, automate complex workflows, and build custom AI agents tailored to their unique enterprise environments. Engineers save hours by asking questions in natural language in their code editor rather than learning and switching between multiple tools, query languages, and dashboards.
Customer outcomes with AI SRE and MCP Server:
- Incident resolution dropped from hours to minutes
- Operational toil and on-call burden reduced
- Observability ROI felt immediately in engineering
o11y.ai is an observability agent that lets developers generate code instrumentation, debug, and ask questions about their application.
Built for developers, o11y.ai makes observability as natural as coding. The agent adds OpenTelemetry instrumentation from day one, giving engineers instant access to the logs, metrics, and traces they need. Developers can ask questions about usage, errors, and performance, as well as debug and validate fixes using context from their telemetry and code.
Customer outcomes with o11y.ai:
- Shorter feedback loops
- Faster root cause analysis
- Higher engineering velocity
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