Solution

Built for regulatory outcomes — not generic data governance

We provide an AI-enabled RegTech platform that automates regulatory data governance across the reporting lifecycle.

• From regulatory requirement to regulatory confidence

• Regulatory requirement → Data → Governance → Evidence

• Map regulatory requirements to reporting data

• Identify material regulatory data across systems

• Apply governance: ownership, lineage, quality controls

• Generate auditable evidence for regulators

• All within a single, regulator-aligned workflow.

Regulatory deadlines are approaching for the Data First Approach

Supervisory expectations for regulatory data governance are increasing globally.

In the UAE, the Central Bank has set clear expectations for enhanced data governance, with compliance milestones extending toward 2029–2030. Similar supervisory pressure exists across the GCC, creating a region-wide need for scalable, automated solutions.

Manual governance approaches will not meet future regulatory scrutiny.

• Built for regulated institutions

• Banks

• Regulated fintechs

• Regulatory reporting teams

• Data governance and compliance functions

If you are accountable for regulatory data, this platform is designed for you.

• Starts from regulatory requirements and reports

• Identifies regulatory-critical data

• Governs data across systems with ownership, lineage, and controls

• Produces audit-ready regulatory evidence

• Automation and AI reduce manual effort while ensuring consistency, traceability, and accountability — with human oversight retained at all times.

• Regulatory data mapping

• Link regulatory requirements to underlying data

• Data dictionary & ownership

• Clear definitions and accountability

• End-to-end data lineage

• Trace data from source to report

• Data quality rules & monitoring

• Detect and manage regulatory data risk

• Audit & evidence management

• Respond to regulators with confidence

• Designed for regulatory reporting and compliance teams.

AI is used to support regulatory data governance through controlled, explainable, and auditable automation, with human oversight and clear accountability aligned to supervisory expectations.