NudgeBee is an AI agents and automation builder for day-2 cloud operations. It focuses on incident investigation, cloud cost reduction, and automated operational work behind a human gate. The product description says it is a unified agentic AI platform for SRE, FinOps, and CloudOps use cases, with a knowledge graph and infrastructure memory intended to keep answers grounded and LLM costs low.
Its pre-built assistants cover several cloud operations tasks. The AI-SRE Assistant investigates alerts to a cited root cause. The AI-FinOps Assistant presents a ranked inbox across AWS, Azure, GCP, and Kubernetes. The AI-K8s Ops Assistant catches pod failures and rightsizes clusters, with changes applied by pull request or one-click approval. The AI-CloudOps Assistant detects infrastructure drift and automates day-2 cloud operations, with every change human-gated. The page also describes a builder for custom automations, including triggers, actions, and control flow with loops, branches, approvals, and sub-automations.
NudgeBee lists 61 integrations and mentions Slack, Jira, PagerDuty, and observability tools among them. It supports triggers from webhooks, HTTP endpoints, tickets, and Kubernetes. Actions include running kubectl commands, running AWS CLI commands, connecting to external services via HTTP or SSH, and searching logs, metrics, and traces from a monitoring stack. It also describes enterprise guardrails, RBAC, approvals, audit trails, and human-in-the-loop controls. Deployment is shown with a Helm install command, and the page says zero telemetry. The product is now open source.
In the Autonomous agents & workflows space, nudgebee takes a focused approach. It focuses on automating and optimizing cloud operations, incident response, and cost management for SRE and FinOps teams using AI agents. nudgebee is an open-source project aimed at SRE, FinOps, and CloudOps teams. The project is open source (Apache-2.0). It ships for the web, and it can be self-hosted.
NudgeBee builds and maintains nudgebee, and it first shipped in 2026. The project is developed in the open on GitHub with 373 stars and 515 commits in the last 90 days. Among its 7 catalogued features are incident investigation, cost optimization, and automation builder. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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