Knowledge base
Practical how-to guides for regulation10.com, the compliance plane for the EU AI Act, 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 or adding an AI system - 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 a notified body - 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 (Owner-only).
- Two-factor authentication and account security - To set up two-factor authentication (2FA), go to Account then Security and enrol an authenticator app: scan the QR code, enter the 6-digit code, and save your one-time recovery codes somewhere safe.
- What the EU AI Act regime is on this platform - Your workspace runs in the EU AI Act regime, so the platform serves EU AI Act corpus, modules, and terminology instead of the DIFC Regulation 10 set.
- EU onboarding and the EU AI Act identity fields - EU onboarding follows the same wizard as elsewhere, with extra EU-specific identity fields so your systems can be assessed correctly.
- What an Annex III high-risk classification means operationally - When a system is classified high-risk under Annex III, the platform unlocks the fuller high-risk obligation set for it: the modules covering risk management, data governance, technical documentation, record-keeping, transparency, human oversight, and accuracy/robustness become applicable, and the system's evidence pack is expected to cover them.
- Finding your EU AI Act obligation status - To see where you stand, open the EU compliance report for a system (or the EU obligation-status view): it lists each applicable obligation, whether the supporting module run and evidence are complete, and what is still outstanding.
- EU AI Act applicability dates and your compliance runway - The EU AI Act phases in on a runway, and the platform tracks the dates for you rather than treating everything as due today.
- How evidence and documents map to EU AI Act obligations - Each EU obligation on a system is backed by the module runs and documents you attach to it.
- Escalating to human support - If the assistant cannot resolve your question, you can reach a person on the regulation10.com team.
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.
- Prohibited-practice (Article 5) screener (Module 1.1b)
- Screen a system against the EU AI Act Article 5 prohibited practices before further assessment.
- 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.