Vailor: the sovereign AI-native GRC alternative to 6clicks
An AI-native GRC platform, built in France, for teams evaluating their governance, risk and compliance options.
Choosing a GRC platform aligned with your requirements
The GRC market offers several platforms, including 6clicks. If you are evaluating your options, Vailor positions itself as a sovereign, AI-native GRC platform built in France for French and European organizations. Our ambition is to make compliance and risk management a smooth and readable process.
What Vailor brings to your teams
Vailor connects risk management and compliance on one foundation: your organisation mirrored entity by entity, fine-grained rights, dashboards and an audit log with no delete function. The AI reads the documents supplied and prefills the risk assessment, in EBIOS RM or in a flash version, and your experts validate. A control assessed once counts for every framework that asks for it. Your data is hosted in France by default.
Evaluate Vailor and plan your migration
You can evaluate Vailor at your own pace and prepare a calm migration from your current tool. Book 30 minutes: we listen to your context, tell you concretely how Vailor answers it and, if it makes sense, scope a pilot. Our team and our integration partners, such as CYNERS, then support the transfer of what you already have.
Why teams choose Vailor
The AI proposes, your experts decide
The AI reads your project documents and prefills the assessment from excerpts. Nothing is validated without a human, and every decision is traced.
Deployment that fits
As SaaS or inside your own infrastructure, depending on your context.
Security by design
Encryption at rest and in transit, a secure development pipeline with continuous image scanning, and SOC-ready logs.
Data sovereignty
Hosted in France by default. Your data never trains any model, and you choose the AI model, including a self-hosted one.
The benefits of sovereign AI-native GRC
Frequently asked questions about multi-client GRC
What does client partitioning mean in multi-client GRC?
Three separate levels. Data isolation between clients first: each organisation and each scope carries its own configuration, frameworks and assets, with no overlap. Internal access rights second: a consultant reaches only the engagements they work on, and that rule has to survive team changes. Traceability last: knowing who produced or changed what, and when. In Vailor each entity carries its own settings, fine-grained rights with custom roles decide who reaches what, and an audit log with no delete function traces every change. The level of separation you need between clients is scoped with you, deployment mode included.
How do you reuse one methodology across different clients?
By separating what is stable from what belongs to the client. Stable: your assessment grid, your likelihood and impact scales, your deliverable formats, your library of controls. Client specific: the scope, the assets, the applicable frameworks, the third parties. Vailor holds that split in its per-entity settings, so every engagement starts from a shared base (scales, matrices, risk sources) and only the context is adjusted. The pre-assessment then qualifies each project: the full EBIOS RM method for a sensitive project, a flash assessment otherwise.
What can genuinely be industrialised, and what stays human?
Industrialised: what is repetitive and checkable. Reading the documents supplied, prefilling the risk assessment, matching requirements against controls, producing the deliverables in PDF, Word or PowerPoint. Human: what carries your advisory responsibility. Scoping the need, deciding which risk is accepted, making the recommendation. The right test is not whether AI can perform a task, but whether you can defend the result in front of your client's steering committee.
How do you keep quality consistent across consultants?
This is the pressure point for a growing practice: the deliverable should not depend on who happens to write it. Two levers. A shared methodological base, applied the same way on every engagement. And AI that quotes the passages of the client's documents it relies on, checked word for word and visible to all, with every proposal counting only once a consultant has validated it. A senior review then covers substance instead of reformatting a document.
How do you steer a portfolio without breaking isolation?
A useful portfolio view is a view of aggregates: progress per engagement, deadlines coming up, open gaps, workload ahead. It does not need the detailed content of any client file to be usable, and that is exactly what makes it compatible with partitioning. The practical rule: visibility across engagements is granted, never inherited. In Vailor, dashboards combine proposed and custom indicators, and access rights decide who gets the overview and who stays on their engagement.
How do you take over client files that are already running?
Engagement by engagement, never as one broad switch. Start with a representative client: switch on the applicable frameworks, bring across the risk register and the controls already in place, run a consistency check, then produce the first deliverable alongside the existing one. That client becomes the template for the next ones, and each takeover gets faster. Settle the history question early: what you genuinely carry over (decisions, dated evidence) and what stays archived where it is. Our teams help scope that.
Explore AI GRC with Vailor
Our resources on governance, risk and compliance assisted by artificial intelligence.
By role, and to go further
Pages to discover
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Discover Vailor in a demo
Book 30 minutes: we listen to your context, tell you concretely how Vailor answers it and, if it makes sense, scope a pilot together.