PagerDuty

What PagerDuty does

PagerDuty provides an AI-first operations platform that offers end-to-end incident management, enabling organizations to ship faster, resolve smarter, and improve operational resilience. The platform leverages AI agents to automate incident detection, diagnosis, and resolution, freeing up teams to focus on strategic work. Built on 16 years of operational data and integrating with over 750 tools, PagerDuty's AI is trained on a deep foundation of failures, fixes, and patterns. It supports full-lifecycle incident management, from proactive detection and response to post-incident reviews and continuous improvement. The PagerDuty Operations Cloud aims to scale teams with AI and automation, driving efficiency, reducing risk, and powering growth across various operational challenges.

Products

• PagerDuty Operations CloudThe platform for AI-first operations, bringing together people and AI to do business-critical operations work that drives efficiency, reduces risk, and powers growth.
• AIOpsReduces alert noise, accelerates triage time, and automates away redundancy by separating signal from noise.
• AutomationEnables operating at machine speed by executing cross-environment automation to shift from legacy systems and ticket speed to automated workflows.
• Incident ManagementManages incidents end-to-end, orchestrating the right people at the right time to resolve critical incidents at speed and scale.
• Customer Service Operations (CSOps)Bridges customer support and engineering teams to deliver outstanding customer experiences through seamless communication.
• PagerDuty AdvanceLeverages generative AI to deliver useful recommendations and insights, empowering teams to resolve incidents faster and more efficiently. Includes AI Actions.
• AI OrchestrationsAnalyzes historical event and incident data as well as responder behavior to recommend Event Orchestration rules for proactive, event-driven automations.
• Runbook Automation/RundeckModernizes the platform with Grails 7, Spring Boot 3, and Java 17 support, delivering improvements across performance, security, and user experience. Turns manual tasks into automated routines.
• Scribe AgentEnriches Incident Workflow actions, such as adding Google Meet bridges with automatic transcription and posting Periodic Incident Progress updates to incident channels.
• Insights AgentAvailable in Microsoft Teams and Slack, allows users to ask plain-language questions to quickly surface insights and trends from PagerDuty incident, service, and team analytics.
• SRE AgentActs as a virtual responder, detecting issues, diagnosing root causes, and orchestrating fixes automatically. Enhances triage with new connectivity and capabilities.
• On-Call ManagementProvides intuitive, flexible scheduling and escalations for rapid response.
• Stakeholder CommsShares information about incident impact and progress towards resolution.
• JeliTurns every incident into an opportunity to learn through incident analysis.
• Mobile AppAllows viewing, discovering, and responding to critical incidents from anywhere, at any time.
• Status PagesShows an organization's operations current state and proactively communicates to the audience.
• Incident WorkflowsBuilds an automated response for every incident.
• Distributed AutomationSecurely connects automation to remote environments via the Enterprise Runner.

Key capabilities

• AI Agents (SRE Agent, Scribe Agent, Insights Agent, Shift Agent)
• AI-first operations platform
• End-to-end incident management
• 750+ integrations
• Automated responses and workflows
• Root cause diagnosis
• Orchestration across tech stack
• ML-driven noise reduction (91% cut in noise)
• Real-time collaboration (Slack, Microsoft Teams)
• Customizable workflows
• Post-incident reviews (AI-generated drafts)
• Intelligent Service Mapping for Backstage Plugin
• On-call scheduling and escalation policies
• Alert severity and custom incident actions
• Service Directory
• Dedicated Incident Channels in Slack
• PagerDuty agent app in GitHub (live incident state, history, change correlations)
• Extensive APIs
• Proprietary Foundational Data Model
• Embedded AI/ML & GenAI
• No-Code to Pro-Code Automation
• Zero Maintenance Availability Window
• Automated remediation
• Guided remediation
• Continuous improvement from incident learnings
• Self-Service Automation
• Security and Compliance (built-in guardrails, authentication, context-based permissions, audit trails)
• FedRAMP® Low Authorized
• SOC 2 Type II Certification
• ISO 27001 Certification

Use cases

• End-to-end incident management
• Proactive incident management
• Automating critical work across the enterprise
• Learning from previous incidents to build resilience
• Operations Center Modernization
• Automation Standardization
• Customer Experience Operations
• Digital Operations Resiliency
• Scaled Service Ownership
• Remote-Location Operations Automation
• AIOps (separating signal from noise, accelerating triage)
• Incident response (orchestrating people for critical incidents)
• Automation (executing cross-environment automation)
• Customer service operations (bridging support and engineering)
• LLMOps (managing efficient LLMs, ensuring reliability and safety)
• DataOps (optimizing data usability and value at scale)
• CrisisOps (preserving company reputation and customer trust)
• FinOps (controlling cloud costs, reducing risk, resolving unplanned issues)
• ComplianceOps (maximizing regulatory adherence and operational integrity)
• Security incident management (mobilizing right people, standardizing processes, learning from security incidents)
• DevOps automation (continuous delivery, patching, customer tenant operations)
• Service operations (ITSM) (standardizing SOPs, SOC2 audits, change tracking, multi/hybrid cloud ops)
• Self-service requests (developer operations, system access requests, data collection)
• Event-driven automation (service diagnoses, incident remediations, triggered maintenance)
• Incident remediation (pre-built automation jobs)
• Edge automation (device restart & reconnect, update local firewall settings, retrieve logs)
• Kubernetes Operations (managing deployments, job operations, debug state capture)
• Continuous delivery (increasing release velocity)

AI approach

PagerDuty leverages AI and ML, including proprietary models and generative AI, to automate incident management, reduce alert noise, diagnose root causes, orchestrate fixes, and provide insights. Their AI agents (SRE Agent, Scribe Agent, Insights Agent, Shift Agent) handle tasks like incident detection, triage, documentation, scheduling, and trend analysis. The platform is built on 16 years of operational data and integrates with various tools, using a Model Context Protocol (MCP) for AI-enabled tools. They emphasize using AI for specific problems and continuously learn from incidents to improve their models.

Tech named: AI, ML, Generative AI, SRE Agent, Scribe Agent, Insights Agent, Shift Agent, AI Orchestrations, PagerDuty Advance, LLMOps, Model Context Protocol (MCP)

Industries served

• Technology
• Financial Services
• Healthcare
• Government
• Nonprofits

What it says sets it apart

• AI-first operations platform with proprietary AI agents (SRE Agent, Scribe Agent, Insights Agent, Shift Agent)
• 16 years of operational data and 750+ integrations for AI training
• Industry's deepest data foundation for AI
• Reduces alert noise by 91% with ML
• Automates incident detection, diagnosis, and fixes
• Full-lifecycle incident management from detection to continuous improvement
• Open, extensible architecture connecting to 750+ tools
• Real-time collaboration within Slack or Microsoft Teams
• AI-generated post-incident reviews
• Intelligent Service Mapping for Backstage Plugin
• FedRAMP® Low Authorized, SOC 2 Type II, ISO 27001 certified
• Focus on operational resilience and continuous learning
• Ability to integrate with existing tools and processes (Bring Your Own Stack)
• Strong focus on security incident management and compliance (DORA, FCA/PRA)