Groundcover Raises $100M to Keep AI Agent Observability Inside the Cloud
Observability startup groundcover has raised $100 million in a funding round led by One Peak, betting that enterprises want to monitor AI agents without letting sensitive telemetry data leave their own cloud environments.
As enterprise adoption of AI agents accelerates, the infrastructure to monitor these autonomous systems is attracting massive growth capital. Observability startup groundcover has raised $100 million in a new funding round led by growth equity firm One Peak. The investment signals a significant bet on the next phase of the AI stack, where monitoring and debugging LLM-driven workflows must balance performance with strict enterprise data privacy.
The round represents a major scale-up for the company, which has built its reputation on a self-hosted, eBPF-powered architecture. While legacy observability giants like Datadog and Dynatrace have dominated the cloud era with ingestion-heavy SaaS models, groundcover's core thesis is that AI telemetry cannot follow the same path. For enterprises deploying proprietary models on highly sensitive corporate data, sending telemetry to a third-party cloud is an absolute non-starter.
By keeping all observability data within the customer's own cloud perimeter, groundcover addresses the primary friction point in enterprise AI deployment: security. The startup's platform allows companies to track the behavior, latency, and cost of AI agents without exposing the underlying prompts or proprietary corporate data. This architectural choice is proving to be a highly bankable differentiator as venture capitalists search for infrastructure plays that can withstand enterprise compliance hurdles.
For lead investor One Peak, the $100 million check is a play on the picks and shovels of the generative AI boom, joining a broader wave of massive capital deployment into AI infrastructure. Rather than funding foundational models with uncertain unit economics, growth investors are increasingly rotating capital into the developer tooling and observability layers that make these models viable for production. As more enterprises move AI agents from experimental pilots to core business workflows, the demand for secure, local telemetry is poised to become a massive market, making groundcover a formidable challenger to incumbent SaaS monitoring suites.