90% Alert Noise Eliminated Before It Reaches Your On-Call Queue
Dedupes and correlates signals, cutting alert volume 90%.
Award-Winning AI Development & Consulting
IT / Engineering
Alert Fatigue and Triage Lag Are Where Downtime Costs Accumulate
Gartner estimates IT infrastructure downtime at $5,600 per minute — yet for most enterprises, 35–45 minutes of that cost is consumed before remediation starts.
Read the full evidence
OpsRamp research shows 71% of IT teams identify alert fatigue as a significant crisis: large enterprises generate 10,000–100,000 monitoring alerts per day, of which 50–70% are noise requiring no human action. The triage phase — determining severity, finding the right owner, and gathering context — is where downtime costs accumulate.
Business impact
90%
reduction in alert noise — filtering 10,000+ raw daily monitoring alerts down to the focused, deduplicated, correlated incident queue your on-call teams actually need to act on
- $5,600
- Triage burns 35–45 of those minutes. We cut it to 60 seconds.
Core Capabilities of the AI Incident Triage Agent
Six capability pillars — from alert ingestion and noise suppression to ML severity classification, routing, and automated remediation.
01
Alert Ingestion & Correlation
Ingests alerts simultaneously from Datadog, Splunk, New Relic, Dynatrace, CloudWatch, Prometheus, Nagios, Zabbix, PagerDuty, and OpsGenie via native connectors — consolidating your entire observability stack into one unified incident stream.
02
Severity Classification & Scoring
Classifies every incident by severity across five dimensions: service criticality, user impact, SLA breach risk, blast radius, and historical resolution urgency.
03
Routing & Context Enrichment
Routes each incident based on CMDB service ownership, historical routing outcomes, on-call availability, team workload, and required technical skills.
04
Automated Remediation & Resolution
Pre-approved library covers common failure patterns: pod crash-loop restart, disk cleanup, DNS flush, SSL renewal, auto-scaling expansion, circuit breaker reset, and service restart.
05
War Room Coordination & Communication
P1/P2 detection auto-provisions a Slack or Teams war room, adds all on-call responders, and posts an immediate brief covering symptoms, affected services, customer impact, and initial root cause hypothesis.
06
Postmortem Generation & Intelligence
Generates a structured postmortem draft at closure from the incident timeline: chronology, affected services, customer impact, root cause, contributing factors, and recommended action items.
Why Engineering and IT Operations Leaders Deploy Bonami's AI Incident Triage Agent
From 40-Minute Manual Triage to 60-Second Automated Context Delivery
Runbook, topology, and on-call owner delivered in 60 seconds.
Known Failure Patterns Resolved Before the On-Call Page Is Sent
Pre-approved fixes auto-resolve 20–40% of recurring incidents.
Integrations
Works With Your Existing Observability and ITSM Stack
The AI Incident Triage Agent connects to leading monitoring, ITSM, and team communication platforms.
7 named systems it connects to
Running something not listed here? Tell us on the call — scoping the connector is the first step.
AIOps Incident Triage Agent
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PagerDuty
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Datadog
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ServiceNow
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Splunk
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Slack
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Jira Service Mgmt
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OpsGenie
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AIOps Incident Triage Agent — FAQs
[ 1 ]
What is AIOps and how does this agent use it?
AIOps uses ML to correlate alerts, classify severity, and auto-resolve incidents.
[ 2 ]
How does the agent differ from a standard monitoring alert system?
Monitoring queues alerts; the agent correlates, triages, and remediates them.
[ 3 ]
How does the alert correlation engine determine that multiple alerts represent the same incident?
It correlates by time, CMDB topology, alert text, and ML on your history.
[ 4 ]
How does the automated remediation system work and what safety controls are in place?
Pre-approved playbooks only, every step logged and haltable from Slack or Teams.
[ 5 ]
Which monitoring, ITSM, and communication tools does the agent integrate with?
Datadog, Splunk, New Relic, CloudWatch, PagerDuty, ServiceNow, Jira, Slack, Teams.
[ 6 ]
How does the agent handle major incidents that span multiple teams and services?
It names a commander, assigns each team, and auto-opens a Slack or Teams war room.
[ 7 ]
What does the postmortem generation produce and how does it feed incident learning?
A structured draft in Confluence, Notion, or ITSM, plus cross-incident patterns.
[ 8 ]
How long does implementation take and what are the prerequisites?
5-7 weeks; needs monitoring APIs, ITSM access, CMDB, and 12-18 months of history.
[ 9 ]
What MTTR reduction and cost savings can we expect from deploying an AI Incident Triage Agent?
Forrester reports 50-75% MTTR cuts and 90% less alert noise.
[ 10 ]
How is this aiops platform different from standalone incident management software or aiops tools?
Incident management software tracks tickets; this aiops platform triages them.
[ 11 ]
Does the agent include alert correlation software, and how does it enable automated incident response?
Yes - built-in alert correlation software drives automated incident response.
Downtime Costs $5,600 a Minute.
Every minute your on-call engineers spend determining severity, finding runbooks, and figuring out which team owns the incident is a minute of downtime cost you are paying for triage rather than remediation. Get a live demo of the Incident Triage Agent running against your monitoring stack and an alert noise audit for your current on-call environment.
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