For operators
Give every client a managed AI readiness service without rebuilding the work for each organization.
See the service modelHow it works
Build AI judgment. Have the evidence ready.
RIVAL turns AI literacy into short practice that fits each role and builds evidence the organization can show when asked.
For people
Practise the AI decisions that matter in your work, a few minutes at a time.
See the role examplesWhy this matters
Make AI literacy demonstrable
Article 4 of Regulation (EU) 2024/1689 requires providers and deployers within the Act’s scope to take measures for a sufficient level of AI literacy among staff and other people who operate or use AI systems on their behalf.
The measures must account for knowledge, experience, education, training, the way AI is used, and the people affected.
Article 2 sets the territorial scope. Article 3 defines providers and deployers. The operative provisions include no organization-size threshold.
Article 113 applied Chapters I and II, including Article 4, from 2 February 2025.
Decisions stay with the organization.
Source: Regulation (EU) 2024/1689, Articles 2, 3, 4, and 113. Open the consolidated regulation on EUR-Lex
The service model
One operator. Several client organizations. Clear boundaries.
An operator can serve many client organizations through one platform. Each organization keeps its own people, context, policy work, and evidence separate.
Operator
The consultant, IT partner, accountant, or other advisory firm that runs the service.
Client organization
The company whose people map AI use, practise decisions, acknowledge policy, and build evidence.
The operator stays recognizable as the service provider. The platform remains visible where delivery and trust require it.
For people
One organization, different kinds of risk
A role profile describes a person’s risk and required practice. A role track supplies the scenarios for that role.
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01
Reception
Decide whether visitor details belong in an AI-assisted email.
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02
Management
Judge whether AI may influence a decision about a person.
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03
Recruitment
Check the conditions before an AI tool summarizes a candidate’s CV.
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04
Communications
Verify a generated public claim before it represents the organization.
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05
Development
Review generated code and protect internal source from unintended disclosure.
Illustrative drill
A small decision, tied to real work
This specimen is illustrative, is not an assignment, and writes no data.
Duration: 30 seconds to 3 minutes.
01 · Situation
You want an AI tool to summarize a candidate’s CV before an interview.
02 · Decision options
A. Paste the CV into the tool. B. Check the approved tool, purpose, and data rules first. C. Ask a colleague to paste it.
03 · Direct feedback
B is the safest first move. Approval and purpose matter before personal data enters a tool.
04 · Transferable principle
Check the tool, purpose, and data before you share information with AI.
How practice adapts
Shared principles, shaped by context
A scenario binds a principle to a risk pattern, situation frame, role, AI tool, and consequence context. One drill renders one scenario.
The AI Readiness Core content pack starts a growing library of principles, role tracks, and scenarios for common work situations.
Mastery reflects how well a person handles one principle. Seniority never reduces practice.
Freshness gives recent practice more weight and schedules repetition when knowledge becomes stale.
A role change switches the role track and schedules a refresh for the new risks.
From action to evidence
Record the action when it happens
- 01Role and context
- 02Short decision
- 03Feedback and adaptation
- 04Evidence event
The evidence ledger records meaningful actions when they happen, instead of asking the organization to reconstruct them later.
A drill answer writes an evidence event and then informs mastery and freshness.
An evidence pack turns that record into a report of who practised what and when.
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