Re-entry.ai is the operational control layer for modern engineering teams. It sits above your existing CI/CD pipeline and intervenes only when risk, incidents, or guard violations occur — staying completely invisible on the happy path.
Every pull request is analyzed in real time using code diffs, file sensitivity, historical incident patterns, and guard thresholds. Re-entry.ai assigns a risk score and takes automated action: blocking high-risk merges, requesting additional reviews, creating tickets, or escalating to stakeholders — all without manual intervention.
As AI coding agents like Cursor, GitHub Copilot, and Claude Code take on more autonomous work, Re-entry.ai provides the governance layer above them. Through the MCP Gateway API, agents can query risk assessments, check guard compliance, and receive allow/block/require-human decisions before executing changes. Every API call is logged in an immutable audit trail.
Human-defined guards are machine-enforced. Define risk thresholds, required reviewers, and automatic actions once — Re-entry.ai enforces them every time. Incidents trigger automated escalation workflows to Slack, PagerDuty, or Jira. Human override is always available, and every action is explained in plain language.
Guardian Mode monitors protected branches using GitHub webhooks for instant detection. The risk engine assesses push events in sub-second response time and creates interventions before damage is done. Configure guards per repository or globally across your organization.
Re-entry.ai is designed for engineering teams using autonomous AI coding agents, teams operating with rapid deployment cycles, and organizations that need governance and compliance without slowing down development velocity. It is not a replacement for GitHub, Jira, or Slack — it sits above them as a risk and intervention layer.
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