New Relic is making a major play for the enterprise AI observability market with a new platform that lets companies build and manage AI agents while beefing up OpenTelemetry data integration. The launch signals how observability vendors are racing to help enterprises monitor increasingly complex AI-powered systems, as companies struggle to track performance and reliability across distributed AI workloads. It's a timely move as enterprises scale up AI deployments and demand better visibility into how their agents actually perform in production.
New Relic is betting big on AI agents. The observability platform just rolled out a new suite of tools that let enterprises create and manage AI agents while significantly improving how they ingest and analyze OpenTelemetry data streams. It's the company's most aggressive push yet into the exploding market for AI infrastructure monitoring.
The timing couldn't be better. Enterprises are deploying AI agents at breakneck speed, but most lack the observability tools to track what these autonomous systems are actually doing. Traditional monitoring falls short when you're dealing with agents that make independent decisions, call multiple APIs, and interact with users in unpredictable ways. New Relic is trying to solve that visibility gap.
The new AI agent platform addresses a critical pain point: enterprises want to experiment with AI agents but need enterprise-grade observability baked in from day one. Instead of cobbling together separate tools for agent creation and monitoring, companies can now build and track everything in one place. That's a compelling pitch for IT teams already drowning in tool sprawl.
But the OpenTelemetry piece might be even more strategic. OTel has become the de facto standard for collecting telemetry data across distributed systems, and New Relic is doubling down on better integration. The enhanced tools promise to make it easier for enterprises to pipe OTel data into New Relic's platform, then correlate it with AI agent performance metrics. That unified view is what enterprises need as their infrastructure gets more complex.
The move puts in direct competition with and , both of which have been aggressively expanding their AI monitoring capabilities. has been pushing LLM observability features, while touts its AI-powered automation. is differentiating by letting customers actually build agents within the platform, not just monitor external ones.
