Trust is built. Governance keeps it alive.

To share data and coordinate AI agents, partners need to know what they commit to, and how their commitments will be followed up.

From principle to practice.

A rulebook sets an ecosystem’s common rules. It becomes useful when it helps participants make decisions, onboard a new partner or handle an incident.

Onecub helps you design this framework and connect it to use cases, contracts and technical mechanisms. The goal: governance that is readable, enforceable and able to evolve.

What is a rulebook? Our FAQ

Decide together.Roles, bodies and decision rights.
Share under conditions.Access, purposes and terms of use.
Act with a mandate.Permissions and limits of AI agents.
Check and evolve.Controls, evidence and rulebook reviews.

Four questions to settle together.

Who takes part and who decides?

Define roles, entry and exit conditions, decision bodies and ways to resolve disagreements. A group must be able to welcome new members without renegotiating all its foundations.

Who can use what, and why?

Specify access rights, purposes, reuse conditions and responsibilities. Link contractual commitments to technical choices, with legal and operational teams.

How are commitments checked?

Turn principles into understandable rules, controls and evidence. Decide what belongs to the contract, to human review or to a technical control, then organise follow-up and changes.

Within what limits do agents act?

Define AI agents’ mandates, permissions and limits. Plan human approvals, traceability of actions and ways to suspend or revoke a delegation.

A common framework.
Deliverables you can use.

Frame

Map stakeholders, use cases, decisions and risks. Identify existing rules and the points to settle.

Role mapping
Diagnosis
Priorities

Formalise

Co-design the group’s rules, onboarding journeys and responsibilities. Keep the rulebook, contracts and permissions consistent.

Governance model
Rulebook
Participant journeys

Put to the test

Test the framework on real scenarios: a newcomer, a change of purpose, an incident, an agent’s action. Plan controls, evidence and rule reviews.

Test scenarios
Control plan
Review cycle

Does your group need a rulebook, or need to evolve one?

Let’s talk about your project

AI acts.
Who gives it a mandate?

With AI agents, governance extends from data to actions. An access authorisation is not enough to define what an agent may decide, on whose behalf it acts, or when a person must take back control.

We address these questions from the design stage: scope of delegation, limits of action, supervision and accountability. A framework to test with your teams before expanding the uses.

Agentic AI for data spaces

Open to cooperation.
Fitted to your ecosystem.

We build on European data space work and open standards to ease interoperability. The framework must reflect your sector, your partners and your business model, without imposing a single technology.

Data spaces, AI agents and digital commons

Rules that hold, for cooperation that lasts.

Let’s talk about your group, its decisions and its commitments.