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Incident Management Automation

Automate L1 operations

BigPanda AI Detection and Response uses real-time signals and automation to detect, diagnose, triage, and resolve issues quickly.

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Automate more, escalate less

Automated incident response improves first-contact resolution, eliminate manual and duplicate L1 workflows, and prevents disruptive escalations.

Proactive incident detection

Automatic incident management helps you spot early signals of issues using AI-driven correlation across observability, service desk activity, and external service provider dependencies. Cut noise and identify critical patterns before incidents escalate.

BigPanda AI-driven correlation filters out noise and surfaces early signals of potential issues before they impact your business.
Enrich incidents with context from historical, change, and CMDB data to surface runbooks and knowledge articles for accurate diagnosis and automated resolution.

Automated incident diagnosis

Automatic incident management enriches every incident with context from historical incidents, recent changes, and CMDB data to automatically surface runbooks and knowledge articles and accurately diagnose incidents.

Faster and smarter triage

Automated incident response instantly assess incident impact and priority, while surfacing root cause analysis and suggested next steps for faster, more confident triage decisions.

Inform L1 operators of the most efficient actions to take during triage and response, verified based on past incident insights.
BigPanda AI response links relevant runbooks and knowledge base articles directly within the incident for L1 review and execution.

More incident management automation, less escalation

Eliminate guesswork and empower L1 teams to resolve incidents quickly with AI-suggested and automated remediation. Escalate issues only when needed and to the right team. Enrich tickets with context so incident responders can act fast.

Take control of incidents before they escalate

Gamma Communications logo

 

“Not only can we see the alerts, but we can evaluate them using correlation that recognizes patterns, connects alerts, and leads to fewer incidents.”

Dan Bartram

Head of Automation and Monitoring
Gamma Communications

Bloor Research logo

 

“Adding context to enrich alert data leads to more effective prioritization, faster problem resolution, and fewer service disruptions.”

Paul Bevan

IT Infrastructure Research Director
Bloor Research

WEC Energy Group logo

 

“BigPanda has enabled us to get more real-time, relevant data about a specific incident. This has significantly reduced our mean time to resolution (MTTR).”

Steve Liegl

Director of Infrastructure and Operations
WEC Energy Group

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FAQ

What types of data can I integrate into BigPanda?
BigPanda can ingest data from various internal and external sources, including monitoring and observability data, historical data such as incident records, knowledge bases, runbooks, external observability, and service desk data.
How does BigPanda provide additional context for enterprise ITOps?
BigPanda enriches incidents with relevant context by ingesting and normalizing data from diverse sources, including topology, CMDB, and change data.

BigPanda multidimensional alert correlation and AI incident analysis provide you with deeper insights and automate root cause analysis (RCA) for quick, informed decision-making.

This comprehensive approach enables you to resolve incidents efficiently with a holistic view of your system interconnectivity and operational impacts.

Does the AI learn and adapt?
Yes. AI agents recommend or automate remediation based on incident context by leveraging your institutional and informal knowledge—even if it’s undocumented. Real-time insights enable systems to learn from past incident resolutions and adapt dynamically, reducing your reliance on manual escalation.

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ANALYST REPORT

Gartner® Market Guide for Event Intelligence Solutions, 2025

According to Gartner®, I&O leaders should use this research to separate the hype of AIOps from the achievable value of optimized operations, reduced toil, and improved performance and availability.

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