AI Incident Prevention (IP)
BigPanda AI Incident Prevention helps teams stop change-related incidents before they happen with scalable, proactive change and problem management.
Instead of reacting to outages after they occur, AI Incident Prevention uses AI-driven analysis of operational and change data to predict potential problems and guide teams toward safer, more reliable deployments.
By analyzing historical incidents, change activity, and operational signals, the platform helps teams proactively reduce operational risk and strengthen the stability of their services.
Full feature list
For a full list of documentation for features in the AI Incident Prevention web app, see the Navigate the Web App documentation.
How AI Incident Prevention helps
AI Incident Prevention helps teams move from reactive incident management to proactive operational improvement. By providing AI-powered insights across change data and incident history, teams can make safer decisions and prevent outages before they affect users.
With AI Incident Prevention, organizations can:
Identify high-risk changes before they are deployed
Reduce recurring incidents by uncovering systemic issues
Prioritize remediation efforts based on impact and risk
Improve service reliability with data-driven operational insights
Strengthen change and problem management processes
By combining AI-powered change analysis, root cause detection, and operational insights, AI Incident Prevention enables teams to shift from reactive incident response to proactive incident prevention.
Key features
Change Risk
Problem Management
Change risk management
Changes to infrastructure and applications are one of the most common causes of service disruptions. AI Incident Prevention helps organizations evaluate the risk associated with planned changes before they reach production.
The Change Risk Dashboard analyzes change request details and compares them with historical change and incident data to calculate a risk score for each change.
This allows teams to:
Detect potentially risky changes early
Understand why a change may introduce risk
Take mitigation steps before deployment
By identifying high-risk changes in advance, organizations can prevent outages and reduce operational disruption.
Problem management
The Large Context Analysis dashboard gives your team AI-powered Problem Management. Use the dashboard to equip your teams with powerful root cause and trend analysis, as well as recommended actions, so they can confidently remediate recurring incidents, prioritize resources, and improve the reliability of your services.
Using AI-powered analysis across operational data and incident history, the platform detects patterns and trends that may indicate underlying problems in the environment.
By addressing the root causes of incidents and not just their symptoms, organizations can break the cycle of repeated outages.
Analytics and risk visibility
AI Incident Prevention includes dashboards and analytics that provide visibility into change risk and operational trends.
These dashboards help teams monitor how changes impact their environment and track improvements over time. For example, analytics views can show overall change risk posture, risk trends, and other insights that help organizations evaluate the effectiveness of their change management practices.
By providing a centralized view of risk and operational trends, these dashboards help teams continuously improve their reliability practices.
AI Incident Prevention Documentation
The following features are available as part of AI Incident Prevention:
Next Steps
Learn how to configure AI Incident Prevention