Knowledge base
Practical how-to guides for regulation10.ae, the compliance plane for DIFC Data Protection Regulation 10, plus a reference of the compliance modules the platform runs. Every guide is the same source-grounded content the in-product assistant cites.
Guides
- Onboarding and choosing your subscription tier - To onboard, create your account, verify your email, then complete the onboarding wizard: name your organisation, set your residency region, and choose a subscription tier (Starter, Growth, or Enterprise).
- Registering an AI system, and how to edit or change its owner and other details - To register an AI system, open the AI Systems page and click Register a system (or Add system).
- Running a compliance module and getting a report - To run a compliance module, open a registered AI system, pick a module from the module list, and start a run.
- Generate an evidence pack and share it with an ACB - To produce an evidence pack, open the AI system and click Generate evidence pack.
- Managing team members and in-app roles - To manage your team, open Team (or Members) in settings.
- Billing, invoices, and changing your plan - Billing lives on the Billing page, which only the workspace Owner can see.
- Two-factor authentication and account security - To set up two-factor authentication (2FA), go to Account, then Security, and enrol an authenticator app.
Compliance modules
These are the modules you run against each registered AI system. They are included in your subscription tier rather than sold individually.
- AI system risk classification (Module 1.1)
- Classify each registered AI system by risk so the right obligations and modules apply to it.
- Data protection impact assessment (Module 1.2)
- Draft and score a data protection impact assessment for a registered AI system.
- Transparency notice (Module 1.3)
- Generate the transparency notice a system needs for the people it affects.
- Bias and fairness testing (Module 2.1)
- Assess a system for bias and fairness and record the findings against it.
- Threat modelling (Module 2.2)
- Build a threat model for a system and capture the mitigations in its evidence.
- Red-team assessment (Module 2.3)
- Run a structured red-team assessment against a system and score the results.
- Model drift monitoring (Module 3.1)
- Track model drift over time so a system's performance stays inside its expected bounds.
- Complaint intake and SLA (Module 3.2)
- Take complaints about a system, start the acknowledgement clock, and record the trail.
- Tamper-evident audit trail (Module 3.3)
- Keep a tamper-evident audit trail of everything done to a system and its evidence.
- Evidence pack generation (Module 4.1)
- Assemble completed module runs, artefacts, and the audit trail into a single evidence pack.
- Framework crosswalk (Module 4.4)
- Map a system's evidence across frameworks so one body of work answers several regimes.