New Relic launches new AI agent platform and OpenTelemetry tools
The data observability company enters the crowded AI agent platform race with a specialized, no-code offering.
New Relic has entered the competitive AI agent platform market with the launch of its New Relic Agentic Platform. This no-code platform is specifically designed for enterprises to build, deploy, and manage AI agents that monitor data observability to proactively catch bugs and system issues. A key technical feature is its support for the Model Context Protocol (MCP), which standardizes connections between AI applications and external data sources, facilitating integration with other tools in the ecosystem.
Unlike general-purpose platforms from OpenAI (Frontier) or Salesforce (Agentforce), New Relic's offering is narrowly focused on observability outcomes. According to Chief Product Officer Brian Emerson, the goal is not to be the sole platform for all AI agents, but to provide specialized agent-building capabilities within the observability domain that can interoperate with other tools. This reflects a strategic move to embed AI deeply into its core product suite.
Concurrently, New Relic announced significant OpenTelemetry (OTel) enhancements. Its Application Performance Monitoring (APM) agents now have native OTel capabilities, allowing enterprises to manage OTel data streams alongside other telemetry data in a single platform. This addresses a major fragmentation pain point that has hindered broader OTel adoption, as noted by CTO Strategist Nic Benders, by reducing the operational burden of running separate OTel data collectors.
- Launches a no-code AI agent platform specialized for data observability, supporting the Model Context Protocol (MCP).
- Enhanced APM agents with native OpenTelemetry capabilities to consolidate data streams and simplify fleet management.
- Positioned as a specialized tool for observability outcomes, designed to interoperate within a broader ecosystem of AI agent platforms.
Why It Matters
It provides a specialized, integrated path for enterprises to deploy actionable AI agents for system reliability, reducing observability complexity.