Execution Platform
Unified data, services, workflows and agents in one operating substrate.
Data Resilience Recovery is part of the Advanze platform layer: the execution foundation that enables applications, services and AI agents to work as one operating system for the business. It is designed for extensibility, governance and scale from the start.
Execution Platform / Data Resilience Recovery
Advanze is positioned around the idea that enterprise software must evolve from passive systems of record into active systems of execution. In that model, this page is not just a feature description. It explains how Data Resilience Recovery contributes to an operating environment where people define intent, agents execute governed work, and leadership can see progress through unified data.
The value is strongest when the capability is connected to adjacent processes. Records, workflows, controls, communications and analytics should not live in separate tools. They should participate in a shared execution fabric that can coordinate work across departments while preserving human accountability.
Core capabilities
Each capability is designed to work as part of the broader execution platform rather than as a disconnected module.
Restore data to defined points within the configured retention window without full database restore. Transaction-level recovery precision targets specific data changes for surgical rollback. PITR built into every table automatically without manual backup configuration.
Automatic snapshots capture full database state at configurable intervals. Incremental backups between snapshots minimize storage costs and recovery time. Backup data encrypts at rest and replicates to multiple regions.
Deleted records move to soft delete state instead of immediate removal. Recovery window allows restoration of accidentally deleted data before permanent purge. Automated cleanup jobs reclaim storage after retention period expires.
On-demand snapshots capture database state before risky operations like schema migrations. Named snapshots tag important milestones for easy identification. Snapshot retention policies balance compliance requirements with storage costs.
Multi-region replication ensures data survives regional outages or catastrophic failures. Automated failover switches to backup region within minutes. Recovery time objective and recovery point objective meet enterprise service targets.
Automated recovery drills validate backup integrity without impacting production. Test restores to isolated environments verify data recoverability. Compliance reports demonstrate ability to meet regulatory recovery requirements.
Agentic operating model
Advanze treats AI agents as participants in the operating model. Agents can read context, call services, update records, trigger workflows, prepare decisions and escalate exceptions. Human teams remain responsible for judgement, governance and business accountability.
That distinction matters. The goal is not to add another chatbot to existing systems. The goal is to create an execution platform where work can move across functions with consistent permissions, policies, audit trails and data visibility.
Business outcomes
Agentic use case
A bad import or system change has corrupted business records.
What makes it harder in the real world: Data correction requires evidence, impact analysis, ownership, approval, rollback choice, downstream notification and audit trail. A fast fix without traceability can make the incident worse.
What Advanze changes: Detect bad data, classify impact, identify the source, route approval and restore or correct records with auditable point-in-time recovery.
Data correction requires evidence, impact analysis, ownership, approval, rollback choice, downstream notification and audit trail. A fast fix without traceability can make the incident worse.
Detect bad data, classify impact, identify the source, route approval and restore or correct records with auditable point-in-time recovery.
Detect bad data, classify impact, identify the source, route approval and restore or correct records with auditable point-in-time recovery.
Why AI execution needs architecture
That is why the Advanze control model matters: identity, permissions, policies, workflow, audit evidence and human judgement are embedded into execution before agents act.
Implementation path
Advanze can be introduced progressively. The recommended path is to start with a visible workflow, prove the operating model, then expand into adjacent capabilities as the platform foundation matures.
Map the workflows, systems, data sources and manual coordination points around this capability.
Define the data model, human approvals, agent tasks, service calls and governance controls.
Start with a bounded use case that proves the operating pattern and creates reusable platform assets.
Extend the pattern to adjacent workflows, more agents, more users and deeper integrations.
Next step
Explore how Data Resilience Recovery can be implemented as part of a broader Advanze platform adoption programme, from first pilot to enterprise scale.
