Comparer
AIRegistra face aux alternatives — honnêtement.
Trois comparaisons : suites GRC entreprise, tableurs, outils internes maison. On dit où AIRegistra gagne, où il perd et où ça dépend.
Matrice fonctionnelle
Côte à côte
Onze dimensions sur lesquelles les acheteurs mid-market comparent. Les cellules cherchent à être spécifiques plutôt que flatteuses.
| Dimension | AIRegistra | Enterprise GRC OneTrust · Drata · Vanta | Spreadsheets / Notion Spreadsheets · Notion · Airtable | DIY internal DIY internal tools |
|---|---|---|---|---|
| Starting price | €4.99 / user / month (design partner) · €7.99 standard | Annual contract; mid-five to six figures typical | €0–€10 / user / month | Engineering time; ~€20–60k initial build, ~€10k/year maintenance |
| Time to first audit-ready output | ~10 minutes for first snapshot | Weeks to months; usually requires implementation services | Immediate | Weeks to months — first useful version, never finished |
| Tool registry | Centralized inventory of every AI tool — vendor, classification, sensitivity, owner, status. | Treats AI tools as another row in a generic vendor inventory — not AI-aware out of the box. | Hand-curated; goes stale fast as people add tools without updating the sheet. | Whatever schema you design — and re-design as the tool stack changes. |
| EU AI Act-specific content | Per-role checklist, evidence types, snapshot PDF | Generic GRC frame with AI overlay; depth varies by vendor and module tier | You build it; the spreadsheet has no opinion | Whatever you build; the regulatory expertise is your responsibility |
| AI-as-product-feature tracking | Yes — provider role + AI-feature tracking native | Limited — most products treat "AI tool" as another vendor record | Whatever you can fit in columns | Customisable but you build it |
| Per-team budget tracking | Native — budgets per team, 75/90/100% threshold alerts, multi-currency normalisation via cached ECB rates. | Spend tracking via separate FP&A integrations rather than native; per-team allocation usually inherited from finance system. | Whatever formulas you write. Brittle once teams rename or split. | Customisable; tied to whatever finance system you already use. |
| Tool-adoption workflows | Request-approval routing configurable per data class and cost; rationale logged on every decision. | Workflow capability is broad but generic — configurable for compliance approvals, not AI-policy-aware out of the box. | Email + comments + the goodwill of whoever owns the sheet. | Configurable to your taste — but integrating with your AI policy is your job, not the tool's. |
| Role-based access control | Owner / Admin / Member / Viewer at the org; per-team membership; enforced at the platform-rules layer. | Comprehensive — designed for enterprise org structures, granular permissions, often LDAP/AD-driven. | File-level only; everyone with access can edit unless you wire row-level protection by hand. | Whatever your auth layer enforces — typically partial; row-level rules are usually missing. |
| Audit trail | Per-record change history, CSV export | Comprehensive; designed for enterprise audit | Limited — version history at best, no per-record diff | Custom — typically partial coverage |
| Billing-platform imports | Generic CSV import — accepts all common formats from billing platforms. | Extensive; SSO, identity, ticketing, ITSM, billing | Manual paste, occasional Zapier | Whatever you wire |
| Target segment | Any size, mid-market focus | Enterprises (typically 500+) | Any size — and most companies start here | Any size — common in companies with strong internal-tools culture |
Enterprise GRC
vs OneTrust · Drata · Vanta
Broad enterprise governance, risk, and compliance suites that have added AI modules.
OneTrust, Drata, and Vanta are credible choices when you already need broad GRC tooling — SOC 2, ISO 27001, multi-framework audit, vendor risk at enterprise scale. Their AI modules are real and deepening, but their centre of gravity is broad compliance, not AI specifically. For a company that mostly needs AI Act readiness with a fast time-to-value, the price floor and onboarding overhead are usually misaligned with the problem. AIRegistra is narrower, cheaper, and faster to first audit-ready output — but if you already run on one of these platforms or are heading enterprise-scale broadly, integrating AI governance into the existing stack often beats running a parallel tool.
Spreadsheets / Notion
vs Spreadsheets · Notion · Airtable
The default starting point. Free, immediate, infinitely flexible — and infinitely fragile at audit time.
A well-maintained spreadsheet is fine evidence in early stages. The fragility shows up when (a) the spreadsheet has lived long enough to have ten owners, none of whom remember what column G means, (b) an auditor asks for a defensible export and the spreadsheet has no per-record history, or (c) you need to link tools to training records and discover relational data is the wrong shape for a flat sheet. Most companies stay on spreadsheets longer than they should. The right time to move off is not when the spreadsheet breaks — it is when you notice yourself reconstructing what changed last quarter from email threads. AIRegistra is opinionated about the data model and the audit history; the spreadsheet stays nimble and free.
DIY internal
vs DIY internal tools
A custom-built internal tool — usually a low-code platform or a bespoke web app on top of a relational database.
DIY makes sense when (a) you have a clear data model nobody else solves and (b) you have engineering bandwidth to maintain it through a long tail of regulatory changes. The honest case for it: you control the schema, the UX matches your team's mental model, integrations are exact. The honest case against: by month 6, the tool is half-finished, the original author has moved teams, and the EU AI Act has updated three times. Companies that try DIY for AI governance usually end up rebuilding two-thirds of what AIRegistra ships. The exception is companies whose AI governance has unusual constraints (sovereign cloud, custom audit framework, regulator-specific reports) — there, DIY can be the right answer.
Comment cette page a été écrite
Les pages de comparaison ont mauvaise réputation parce que la plupart sont injustes envers les concurrents. On a essayé de faire autrement.
- Quand AIRegistra est réellement moins bon (par ex. largeur face à un GRC entreprise), on le dit.
- Quand AIRegistra est réellement meilleur (prix, time-to-value mid-market, focus EU AI Act), on le dit.
- Aucun concurrent n'est nommé de façon trompeuse. Quand plusieurs produits couvrent une catégorie, ils sont regroupés.
- Si vous trouvez une erreur, écrivez à hello@airegistra.com — on met à jour la page quand on est corrigé.
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