Privaro

We use Privaro to protect personal data in our AI-powered customer support chatbot. Before Privaro, we had no real control over what left our systems when the chatbot processed conversations that often include names, emails, and identity details used to verify authorship claims.

What we liked most: reversible tokenization. Most PII tools just redact data, which breaks the chatbot's ability to actually reference user details mid-conversation. Privaro tokenizes it, lets the model work normally, and restores the real data in the response — so nothing changed in how our support flow works, but now every interaction is protected and logged.

Setup was straightforward, and having an audit trail we can actually show if a customer or regulator asks "what did the AI see" gives us real peace of mind, not just a policy document.

Great to see Privaro launching on Uneed! What I find most important is making AI governance operational: knowing how AI is being used, where sensitive data is involved and having the controls to protect it without adding unnecessary friction for teams.

AI has become part of everyday work incredibly quickly, and that makes it very easy to forget how much information we share with these tools. I love that Privaro approaches the problem without trying to stop people from using AI — the focus is on making that usage safer and more controlled.

From a development perspective, one of the most interesting aspects of Privaro is integrating protection directly into the AI pipeline. Sensitive data can be detected and protected before model ingestion instead of relying entirely on the user to avoid exposing it.

Una de las conversaciones más interesantes que mantenemos con las empresas ya no gira en torno a si deben adoptar la IA, sino a cómo pueden escalar su uso manteniendo al mismo tiempo el control sobre la información corporativa y sensible. Ese es precisamente el problema que Privaro está diseñado para resolver.