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Rootly

AI-native incident management and on-call platform that automates response, streamlines collaboration, and accelerates resolution for engineering teams.

Product Overview

What is Rootly?

Rootly preview

Rootly is a modern incident management platform built natively for Slack, designed to automate the end-to-end incident response process for fast-moving engineering and SRE teams. Leveraging deep AI integration, Rootly orchestrates the entire incident lifecycle—from alerting and on-call scheduling to real-time collaboration, workflow automation, and post-incident retrospectives. With robust integrations, customizable workflows, and AI-powered insights, Rootly reduces manual overhead, ensures consistency, and empowers teams to resolve incidents faster while improving reliability at scale.


Key Features

  • AI-Powered Incident Response

    Automates incident detection, triage, and resolution with generative AI—providing proactive troubleshooting tips, real-time summaries, suggested mitigation steps, and automated documentation throughout the incident lifecycle.

  • Seamless Slack Integration

    Enables teams to manage incidents entirely within Slack, including automated channel creation, role assignments, notifications, and collaboration without switching tools.

  • Customizable Automated Workflows

    Allows teams to automate repetitive tasks such as creating Jira tickets, spinning up video bridges, updating status pages, and managing escalations based on flexible triggers and conditions.

  • Comprehensive On-Call Management

    Consolidates on-call scheduling, escalations, and overrides across multiple clouds, with intuitive interfaces and native time zone support.

  • Deep Integrations Ecosystem

    Connects with popular tools like PagerDuty, Jira, GitHub, and monitoring platforms, enabling seamless data flow and reducing context-switching during incidents.

  • Automated Post-Incident Reviews

    Generates incident timelines, postmortem documents, and actionable insights using AI, streamlining learning and continuous improvement.


Use Cases

  • Engineering Incident Response : Accelerate detection, triage, and resolution of production incidents with automated workflows, AI guidance, and real-time collaboration.
  • On-Call Operations : Simplify on-call scheduling, escalations, and handoffs across distributed teams, ensuring rapid response to critical events.
  • Automated Postmortems : Streamline retrospective analysis with AI-generated timelines, summaries, and recommended action items for continuous reliability improvement.
  • Stakeholder Communication : Keep stakeholders informed with automated status updates, summaries, and public/private status pages during and after incidents.
  • Compliance and Audit Readiness : Maintain detailed incident logs, audit trails, and documentation to support compliance and operational transparency.

FAQs

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