GRC platforms born in the SaaS era digitized compliance. In the post-ChatGPT era, the goal is no longer to digitize GRC, but to solve it with AI.
Legacy GRC tools moved teams from Excel to more modern interfaces or SQL spreadsheet wrappers. That was real progress, but designed before ChatGPT, when AI's potential was still unproven. The result: digitized processes, without changing the nature of the work.
GRC is a deeply textual, documented and standards-driven world: frameworks, policies, evidence, questionnaires. That is precisely the playground of large language models. The potential is massive, provided the platform is designed for AI rather than a chatbot bolted onto the existing stack.
We are past the ChatGPT era: AI's potential no longer needs proving. Merely digitizing GRC is now outdated, and turning to such a solution would be a mistake when platforms genuinely solve it with AI. Vailor was born after ChatGPT, AI-native end to end: we don't digitize anymore, we solve.
Vailor was designed from scratch for AI. Where legacy bolts on an assistant, AI structures every module here.
We don't just replace Excel with an interface: AI does the analysis, mapping and drafting work itself.
EBIOS RM, NIS 2, DORA, ISO: AI accelerates while keeping rigor, with traceable, sourced deliverables.
Hosted in France, deployed as SaaS, on-prem or air-gapped, with an architecture that won't need rebuilding.
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