DataAgent raises $10M to let AI fix production faults inside Kubernetes clusters

Israeli startup DataAgent Ltd. has come out of stealth with $10 million in pre-seed funding and a bold pitch: let AI repair production faults inside a customer’s own Kubernetes clusters, instead of just spotting them and paging an engineer.

The company was started in January by Ishay Yaari, its chief executive, and Nati Shalom, its chief technology officer. Both previously worked at Cloudify Platform Ltd., the open-source cloud orchestration company that Dell Technologies acquired in 2023 for a reported $100 million.

DataAgent is taking aim at a familiar cost trap. Traditional observability tools watch systems, send logs and metrics to a vendor’s cloud, then hand off the problem for a human to investigate. Grafana Labs said in its 2025 observability survey that this kind of spending averages 17% of total compute infrastructure spending, with 10% the most common answer.

DataAgent flips that sequence. Its agents look at live system state, topology and configuration drift where the data already sits, figure out what caused the incident, and then apply a fix that the customer has already allowed through its own guardrails. Deeper root-cause analysis happens later, offline, after service is back. The company says that order is what cuts mean time to resolution.

The platform runs inside cloud-native control planes and sits on top of a customer’s existing monitoring stack rather than replacing it. Data only leaves for deeper inspection when a fault needs it. The agent itself is open source and can be run on its own for free, while a paid SaaS tier handles fleet management and orchestration.

That setup is meant to address enterprise discomfort with closed software in production. DataAgent says customers can cut up to 90% of their observability bill by running its platform alongside existing tools. MizMaa Ventures Ltd. and Alicorn Venture Partners led the round, and DataAgent plans to use the money to push adoption in North America.