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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.

Explore Interactive Demos ↓
◇ Earlier risk signals◷ Faster decisions♧ Resilient operations
LIVE OPERATIONS · ILLUSTRATIVE DEMO AI-ASSISTED
Intelligent recovery control
▤PRIMARY SITEProduction workloadsApplications · Data · VMs
⟶
Protected replicationMonitored data transfer
☁RECOVERY SITEStandby infrastructureRecovery readiness
MonitoringACTIVE
Risk signalsANALYZED
RunbooksCONTROLLED
Example architecture · No connection to live infrastructure
01↗

Predictive Risk Intelligence

Spot warning patterns in performance, capacity and security signals before incidents escalate.

AI-assisted analysis can prioritize anomalies for human review.
02▤

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 WALKTHROUGH

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 RECOVERY

Make complex incidents
easier to understand.

Explore an example of how AI could summarize logs, suggest root-cause investigations and organize a recovery checklist.

✦
KTCHost Recovery AssistantGuided example · not connected to an AI model
DEMO
Why 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.