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Autonomous ITSM · Incident Management
Incident Management, owned by agents.
Detect, correlate, triage, remediate, and close — without paging a human unless policy says so.
78%
Auto-resolved
11.4s
Median resolve time
94%
First-touch accuracy
0
Missed correlations
Legacy way
- Alert floods drown Tier 1 during incidents.
- Analysts hand-correlate across 5 tools.
- Runbooks are stale or buried in Confluence.
- MTTR measured in hours, not seconds.
Authexa way
- Agents ingest telemetry from Datadog, Splunk, PagerDuty in real time.
- Correlate related events into a single incident record.
- Run the right playbook — or write one if none exists.
- Escalate only when confidence or policy require a human.
How the agent handles it
Autonomous loop, end to end.
01
Ingest
Streams from monitoring, endpoint, and comms channels
02
Correlate
Cluster events by CI, service, and blast radius
03
Remediate
Execute playbook · rollback · restart · scale
04
Close & KB
Verify, notify, and file the KB article
Capabilities
Everything the practice needs — detection to resolution.
- Auto-correlation across observability sources
- Blast-radius mapping via CMDB
- Playbook synthesis from prior incidents
- Runbook execution with rollback
- On-call paging with rich context
- Post-incident review generation
- SLA tracking with breach prediction
- War-room orchestration in Slack/Teams
Integrations used
DatadogSplunkPagerDutyOpsgenieSlackMS TeamsGitHubAWSKubernetes
Related modules
See it running on your data.
A 30-minute walkthrough on Incident Management, owned by agents. with your CMDB and top 10 workflows.
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