Enables users to investigate infrastructure incidents in plain English, correlate observability and deploy data with runbooks, and get evidence-backed root-cause proposals with approval-gated remediation.
An MCP-native AI incident response system that empowers agents to investigate production incidents, collect evidence, hypothesize root causes, and drive controlled remediation and recovery verification.
Enables AI agents to safely inspect and execute version-controlled operational runbooks with policy checks, dry-run planning, and out-of-band approvals.
Enables agents to drive an evidence-based approval loop for Bright Data scraper repairs, detecting breakage, generating heal prompts, and verifying fixes against golden rows before commit.
Enables autonomous SRE incident investigation by allowing users to describe incidents in natural language. The agent follows a governed state machine to gather read-only evidence and produce grounded conclusions.
