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Predictive Risk Intelligence
Spot warning patterns in performance, capacity and security signals before incidents escalate.
AI-assisted analysis can prioritize anomalies for human review.Home › Disaster Recovery › AI-Powered Recovery
AI-POWERED DISASTER RECOVERY
Predict. Respond.
Recover Smarter.
Explore how intelligent monitoring, predictive insights and controlled automation can strengthen business continuity and reduce recovery delays.
◇ Earlier risk signals◷ Faster decisions♧ Resilient operations
LIVE OPERATIONS · ILLUSTRATIVE DEMO AI-ASSISTED
Intelligent recovery control
▤PRIMARY SITEProduction workloadsApplications · Data · VMs
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Protected replicationMonitored data transfer☁RECOVERY SITEStandby infrastructureRecovery readiness
MonitoringACTIVE
Risk signalsANALYZED
RunbooksCONTROLLED
Example architecture · No connection to live infrastructure
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Intelligent Real-Time Monitoring
Connect infrastructure, application and log signals to highlight unusual activity sooner.
Surface correlated alerts instead of isolated noise.03⚙
Automated Recovery Response
Use approved runbooks to accelerate isolation, failover and service restoration.
Guardrails and validation remain essential.04✦
Generative AI Recovery Assistance
Summarize incidents, suggest investigations and help document recovery steps.
Recommendations require engineer verification.INTERACTIVE RECOVERY WALKTHROUGHSee AI-assisted recovery
See AI-assisted recovery
in action.
Choose an incident to explore how a team could detect, investigate, recover and validate critical services.
This walkthrough uses predefined sample scenarios. It does not monitor, access or change any real systems.
Scenario: Database FailureSIMULATED DEMO
1Incident detected
2AI-assisted analysis
3Recommended action
4Validation & restoration
Incident response sequence
1
Incident detected
Primary database health checks fail; applications cannot establish connections.
2
AI-assisted analysis
Correlate storage latency, database logs and replica status to identify likely causes.
3
Recommended action
Verify standby consistency and request approval for controlled database failover.
4
Validation & restoration
Check database connections, application transactions and post-failover monitoring.
Scenario health snapshotSIMULATED METRICS
● Primary● Standby● Applications
CPU12%
Memory28%
Storage45%
Connections0
Illustrative recovery workflow4 / 4 stages
Recovery timeScenario-dependent
Data recovery pointPolicy-dependent
GENERATIVE AI IN RECOVERYMake complex incidents
Make complex incidents
easier to understand.
Explore an example of how AI could summarize logs, suggest root-cause investigations and organize a recovery checklist.
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KTCHost Recovery AssistantGuided example · not connected to an AI model
DEMOWhy did the database fail and how can we recover it?
Try the guided incident explanation
Select a scenario or example prompt, then choose “Show Demo Analysis” to see a predefined recovery response.
NEXT STEPS
Build a more resilient business.
Discuss your critical workloads, recovery objectives and opportunities for intelligent operations.