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The AI Operating Layer for Control Assurance.
Most control assurance programs still depend on fragmented systems, manual walkthroughs, spreadsheet-based testing, and inconsistent reviewer interpretation.
Typical assurance cycle
Per RCSA execution
Between visibility checkpoints
ANA uses domain-trained agentic AI to automate the entire control testing lifecycle, from walkthroughs and evidence collection to validation, gap identification, and executive reporting.
ANA uses domain-trained agentic AI to automate the entire control testing lifecycle, from walkthroughs and evidence collection to validation, gap identification, and executive reporting. Built specifically for regulated enterprises, ANA combines intelligent automation with deterministic control logic, audit-ready traceability, and human-reviewed governance.
Structured discovery.
ANA validates whether controls are appropriately taxonomy.
Evidence ingestion at the perimeter.
ANA validates whether controls are appropriately taxonomy.
Validating control design intent.
ANA validates whether controls are appropriately designed to mitigate identified risks, aligning control logic to policy and risk taxonomy.
Sample-based effectiveness testing.
ANA validates whether controls are appropriately taxonomy.
Hidden linkages, surfaced.
ANA validates whether controls are appropriately taxonomy.
Audit-ready output.
ANA validates whether controls are appropriately taxonomy.
ANA is designed to augment assurance teams, not replace governance. Every execution stage includes reviewer visibility, escalation pathways, and traceable audit logic.
Human reviewers validate outputs, observations, and escalations before finalization.
Every testing decision and override remains reproducible under examiner scrutiny.
Source-to-conclusion evidence lineage maintained across all artefacts.
Testing methodology remains transparent, structured, and explainable.
Ambiguous evidence automatically routed for human validation.
Designed for regulatory trust, internal audit defensibility, and governance review.
Not a marginal improvement. A structural shift, from periodic, manual, fragmented control testing to continuous, traceable, AI-driven assurance execution.
Assurance Cycle Time
FTEs per RCSA Cycle
Operational Visibility
Reporting Preparation
Reviewer Consistency
Evidence Coordination
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Every use case is workflow-driven, audit-aligned, and tied to measurable operational pain. ANA isn't a generic AI overlay, it's an execution engine for specific assurance lifecycles.
Automate walkthroughs, testing,
and evidence validation across
financial controls.
Accelerate risk and control self-assessment cycles with continuous assurance workflows.
Validate access, change management, privileged access, and infrastructure controls.
Continuously monitor regulatory controls, policy adherence, and operational risk indicators.
Reduce manual audit coordination while improving testing consistency and documentation quality.
Assess controls across servicing, lending, treasury, payments, and operational workflows.
Surface hidden risk patterns and control gaps before audit discovery.
Deliver centralised assurance visibility across first, second, and third lines of defense.
ANA is deployed securely within your environment, maintaining data ownership, governance controls, and regulatory alignment. Evidence, documents, and assurance outputs remain inside the perimeter throughout the lifecycle.
Direct answers to the questions that surface most often in conversations with CROs, Internal Audit, and Compliance leaders.
RPA executes deterministic tasks via structured inputs.
ANA interprets unstructured evidence — including policies,
emails, reports and communications — and generates
auditable outputs under predefined governance.
Workflow platforms route work. ANA executes the testing itself.
Go deeper on the thinking, the architecture, and the operating model behind ANA.
A complete overview of ANA's architecture, lifecycle stages, governance posture, and deployment model.
Download PDFA practitioner's view of how agentic AI changes the operating model for risk and control functions.
Read white paperHow a regional bank modernised its RCSA cycle and expanded control coverage with ANA.
Read case studyA perspective on the structural reasons assurance functions struggle to keep pace.
Read blogTransform your control environment with ANA, purpose-built for regulated enterprises and deployed entirely within your environment.
