Critical AI process inventory and risk analysis
AI Designed for Continuity
Operational Resilience
We help you keep critical AI and data systems running, make interruption risks visible, and build operational resilience tailored to your sector. Under ISO 22301 we strengthen availability, business continuity, and recovery capability.
ISO 22301
What You Get01 02 03 04 05
ISO 22301
RTO/RPO targets and resilience metrics
ISO 22301-aligned continuity policies
Disaster recovery and redundant architecture
Audit-ready business continuity system
Depth
Resilience Topic Areas
Critical System and Process Analysis
We analyse AI integrations, ML models, and data sources to identify critical processes and threats. The result is a risk strategy aligned with ISO 22301 and ISO 42001, with Trust by Design at the centre.
Setting Resilience Targets
We define RTO and RPO targets suited to your operations so AI services recover within acceptable windows. Recovery plans protect customer experience and critical business functions during outages.
Continuity Policies and Procedures
We prepare business continuity and crisis procedures aligned with regulations including the EU AI Act. AI model behaviour during outages is defined in advance, with clear steps for safe degradation and recovery.
Training and Awareness
People remain the critical link in resilience. We train teams on AI governance, data security, incident response, and human oversight so autonomous errors do not go unchecked.
Resilience Architecture and Controls
We design redundant architecture that activates during outages or attacks. ISO 27001 and ISO 42001 controls are integrated to block threats such as data poisoning or model drift at source.
Performance Measurement and Testing
Business continuity is tested, not just documented. AI penetration tests and disaster recovery exercises validate performance, surface vulnerabilities, and improve resilience capacity.
Verification and Audit Readiness
We verify and document AI processes for independent certification audits. Internal audits close compliance gaps before external assessment and reduce legal and financial exposure.
Continuous Improvement
We run PDCA cycles on continuity systems so your AI governance stays current as threats and regulations evolve.
FAQ
Questions About Operational Resilience
Why is business continuity critical for AI systems?
AI systems often support customer-facing decisions, fraud detection, logistics, and compliance workflows. An outage or model failure can halt operations, damage trust, and trigger regulatory reporting obligations. Business continuity planning ensures AI infrastructure recovers within defined timeframes and keeps operating safely during disruptions.
What are RTO and RPO in the context of AI operations?
Recovery Time Objective (RTO) is the maximum acceptable downtime for an AI service. Recovery Point Objective (RPO) is the maximum acceptable data loss window. For AI systems, RTO/RPO must account for model retraining time, inference failover, and data pipeline recovery, not just infrastructure uptime.
How does ISO 22301 apply to machine learning infrastructure?
ISO 22301 requires identifying critical processes, setting continuity objectives, and implementing recovery procedures. For ML infrastructure this includes redundant inference endpoints, backup model versions, disaster recovery for training data, documented failover runbooks, and regular recovery testing aligned with business impact analysis.
What happens to AI models during a disaster recovery scenario?
AION designs recovery procedures that specify which model versions to activate, how to validate outputs post-failover, and when human oversight must intervene. Pre-approved fallback models, cached predictions, and manual override workflows keep AI decisions safe and auditable during partial recovery.
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