PulseGuard: AI-Powered Incident Management That Calls Your Engineers
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PulseGuard: AI-Powered Incident Management That Calls Your Engineers

The 3 AM Problem Nobody Has Solved

It's 3 AM. Your database is melting. PagerDuty sends a notification. Your on-call engineer's phone buzzes on the nightstand — if they even hear it. They fumble for their laptop, VPN in, try to remember which Grafana dashboard shows the right metrics, scroll through runbooks, and maybe fix the issue 45 minutes later.

Meanwhile, your customers are staring at error pages.

We built PulseGuard because we were tired of this cycle. Every incident management tool on the market does the same thing: detect → notify → hope someone wakes up and figures it out. None of them actually help resolve the incident.

The OpsGenie Migration

With Atlassian sunsetting OpsGenie and pushing teams toward Jira Service Management, thousands of engineering teams are looking for a modern alternative. PulseGuard isn't just a replacement — it's a generational leap forward. While OpsGenie was a notification router, PulseGuard is an AI-powered incident responder that actively participates in resolution.

90s
Mean Time to Resolve
<400ms
Voice-to-Voice Latency
9
AI Model Providers
100+
REST API Endpoints

See It In Action

The interactive demo below simulates a real PulseGuard incident lifecycle. Click through the chapters to watch a database failure cascade through your service topology — and see how Voice AI resolves it in 90 seconds.

Voice AI: The Killer Feature

PulseGuard's Voice AI doesn't just notify engineers — it calls them on the phone, explains the incident with full context, and executes remediation tools during the conversation. The AI understands your service topology, has access to runbooks, and can SSH into servers, query databases, and create Jira tickets — all while talking to your engineer.

Natural Voice Conversations

Full-duplex voice with interruption detection (barge-in). The AI uses natural filler phrases while executing tools: "Let me check that for you..." Supports voice cloning with just a 10-second reference clip.

Mid-Call Tool Execution

The AI executes SSH commands, REST API calls, database queries, and creates tickets — all during the phone call. Results are spoken back to the engineer in real-time with full context.

Sub-400ms Latency

The full voice pipeline — Voice Activity Detection → Speech-to-Text → LLM Reasoning → Text-to-Speech — completes in under 400 milliseconds with the right model stack. Sentence-level streaming means responses start playing as the first sentence is synthesized.

Multi-Provider AI

Connect to 9 AI providers: Ollama, vLLM, LocalAI, llama.cpp, OpenAI, Anthropic, Google Gemini, Azure OpenAI, and AWS Bedrock. Configure fallback chains and load balancing strategies per tenant.

Voice Pipeline Architecture

Every millisecond matters in voice AI. PulseGuard's modular pipeline lets you bring your own models — swap any stage to match your latency and accuracy requirements:

Pipeline Stage

Your Choice

Target Latency

Voice Activity Detection

Configurable VAD engine

< 50ms

Speech-to-Text

Any Whisper-compatible STT

< 150ms

LLM Reasoning

Any OpenAI-compatible model

< 150ms

Text-to-Speech

Any streaming TTS engine

< 100ms

Total Voice-to-Voice

Optimized pipeline

< 400ms

Next-Gen: Unified Omni Models

PulseGuard supports emerging omni-models that handle speech-in → speech-out in a single model pass, reducing the pipeline to one stage. With the right hardware, target latency drops to ~200ms voice-to-voice.

Telephony Integration

PulseGuard supports multiple telephony providers for maximum flexibility:

FreeSWITCH Twilio Telnyx Vonage SIP Trunking Inbound IVR

Service Map & Blast Radius

PulseGuard builds a complete service topology of your infrastructure. When an incident occurs, it instantly calculates the blast radius — mapping every downstream service affected by the failure.

Service Dependencies

Track four dependency types: runtime, build, data, and async. Each with latency metrics and protocol specifications.

Priority Tiers

Classify services P0-P5 with automatic escalation rules based on tier. P0 services trigger immediate voice calls to the on-call team.

RED Metrics

Rate, Error, and Duration metrics per service node. Drill down from service → traces → spans for full observability.

Endpoint Monitoring

PulseGuard continuously monitors your services with configurable health checks:

HTTP Checks TCP Checks PING Checks DNS Checks 10-3600s Intervals

Alert Pipeline

PulseGuard's alert pipeline is designed for zero-noise, high-signal incident detection. Every alert goes through deduplication, enrichment, and intelligent routing before anyone gets notified.

Webhook Ingestion

HMAC-SHA256 signed webhooks from Prometheus, Grafana, Zabbix, or custom JSON. Pre-built parsers extract severity, fingerprint, and context automatically.

Smart Deduplication

Fingerprint-based dedup with configurable windows (default 5 min). Occurrence tracking counts how many times each alert fired. No more alert storms.

AI-Powered Enrichment

Each alert is enriched with AI context per webhook source, service map linkage, and root cause suggestions via LLM analysis of related alerts and service context.

Escalation Engine

Multi-step escalation policies with configurable delays and repeat loops. Target resolution across Primary, Secondary, and Manager on-call layers.

Alert Lifecycle

State

Description

Actions Available

OPEN

New alert, awaiting response

Acknowledge, Snooze, Resolve

ACKNOWLEDGED

Engineer is investigating

Resolve, Escalate, Add Note

SNOOZED

Temporarily muted

Unsnooze, Resolve

RESOLVED

Incident closed

Reopen, View Timeline

Notification Channels

Four notification methods with intelligent dispatch:

📱
Push Notifications
📧
Email Alerts
📞
Voice AI Calls
💬
SMS Messages

Smart Voice Dispatch

Voice calls are blocked if the tenant already has an active call — the system falls back to push notifications as a bridge. Configurable concurrency limits (default: 2 concurrent voice calls per tenant) with 1-hour TTL and automatic requeue.

On-Call & Scheduling

PulseGuard's on-call system supports the complexity of real engineering organizations with multi-layer rotations and timezone-aware scheduling.

3-Layer Rotations

Primary, Secondary, and Manager escalation layers. Each layer has its own rotation schedule with configurable handoff times and rotation periods.

Override Management

Temporary overrides for vacations, sick days, or shift swaps. Override windows with start/end times and automatic reversion to the base schedule.

Timezone Support

Follow-the-sun rotations across global teams. Each schedule respects local timezones for handoff times, ensuring engineers are always paged during reasonable hours.

Automation & MCP Tools

PulseGuard's automation engine lets you define conditional triggers that execute remediation actions automatically — or through the Voice AI during a call.

MCP Tool Types

SSH Execution

Execute commands on remote servers directly through the AI. Run diagnostics, restart services, check logs — the AI interprets results and reports back.

REST API Calls

Call any HTTP endpoint: Kubernetes API for pod management, webhook triggers for CI/CD pipelines, or custom internal APIs. Full request/response logging.

Database Queries

Run SQL queries to diagnose issues: check connection pools, find slow queries, verify replication status. Read-only mode available for safety.

Ticket Creation

Automatically create Jira tickets with full incident context: timeline, affected services, blast radius, and remediation steps taken. Bi-directional sync.

MCP Server Management

Connect and manage MCP servers with enterprise-grade reliability:

HTTP Transport WebSocket Transport STDIO Transport Vault-Backed Secrets Circuit Breaker Auto-Discovery 30s Timeout Health Monitoring

Circuit Breaker Protection

Every MCP server connection is protected by a circuit breaker (CLOSED → OPEN → HALF_OPEN). If a tool server becomes unresponsive, PulseGuard automatically stops sending requests and attempts gradual recovery — preventing cascade failures in your automation pipeline.

Automation Rules

Define rules that trigger automatically based on alert conditions:

  • Conditional Triggers — Fire based on severity, service, labels, or custom conditions
  • Tool Chains — Execute multiple MCP tools in sequence with result passing
  • Test Mode — Validate rules in a sandbox before deploying to production
  • Execution Tracking — Every rule execution logged with SUCCESS, FAILURE, or SKIPPED status

Multi-Tenancy & Security

PulseGuard is built from the ground up as a multi-tenant SaaS platform with enterprise-grade security at every layer.

Tenant Isolation

Complete data isolation per tenant. All database queries, queue operations, and API calls are namespaced by tenantId. No data leakage between organizations.

Vault-Backed Secrets

All credentials, API keys, and MCP server secrets are stored in HashiCorp Vault — never in the database. Automatic rotation and audit logging for every secret access.

RBAC

Three built-in roles: Admin, Operator, and Viewer. Fine-grained permissions control who can acknowledge alerts, modify schedules, execute tools, or manage integrations.

Zitadel Authentication

Enterprise SSO via Zitadel with support for OIDC, SAML, and social logins. Multi-factor authentication and session management with configurable policies.

Audit & Compliance

  • Full Audit Trail — Every action logged: alert acknowledgments, tool executions, schedule changes, configuration updates
  • Voice Call Recording — Complete transcripts and recordings of all AI voice calls for compliance and training
  • API Access Logging — All 100+ API endpoints log request metadata with tenant context
  • Incident Timeline — Detailed timeline for every incident showing escalation steps, notifications, and resolution actions

Architecture at a Glance

30+
Database Models
5
Async Worker Queues
20
Frontend Pages
4
AI Model Purposes

AI Model Allocation

Purpose

Configuration

Context

Voice Conversations

Any OpenAI-compatible LLM

Configurable context window

Alert Summarization

Configurable per tenant

LLM analysis

Root Cause Reasoning

Configurable per tenant

Related alerts + service context

Semantic Embedding

Configurable per tenant

Alert dedup + similarity

Load Balancing Strategies

PulseGuard supports four load balancing strategies across AI model providers:

PRIORITY ROUND_ROBIN REGION_BASED COST_OPTIMIZED

With ordered fallback chains — if the primary model provider goes down, PulseGuard automatically fails over to the next provider in the chain with zero downtime.


Why Teams Choose PulseGuard

OpsGenie Migration

With Atlassian sunsetting OpsGenie, teams need a modern alternative. PulseGuard offers a smooth migration path with API compatibility and feature parity — plus Voice AI that OpsGenie never had.

Self-Hosted Option

Deploy PulseGuard in your own infrastructure for complete data sovereignty. All AI models can run on-premises via Ollama, vLLM, or LocalAI. No data ever leaves your network.

Developer-First API

100+ REST API endpoints with comprehensive documentation. Everything in the UI can be automated via API. Webhook-first architecture for seamless integration with your existing tools.

Ready to modernize your incident management?

PulseGuard transforms incident response from a manual, stressful process into an AI-assisted, automated workflow. Your engineers sleep better. Your customers see fewer outages. Your MTTR drops from hours to seconds.

Book a demo →

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