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The challenge
Thousands of enterprise customers shared the same worry: if an AI agent can read sensitive data, who controls what it sees? Each needed its own protected environment, its own rules, and its own usage reports. No ready-made tool did all of that at that scale.
Most tools block or replace sensitive fields — a name becomes [REDACTED], an account number disappears. That works for simple reports but starves an AI agent of the context it needs to summarize, analyze, or decide. The output becomes unreliable.
Enterprise AI adoption doesn't stall because of model quality. It stalls because security teams can't see what data the agents are touching. Protecto gave our customers the control layer they needed to move forward.
No custom engineering. No extra infrastructure per customer. Four reasons it landed with both the platform team and their customers’ security reviewers.
A new protected environment is a single API call — each customer gets its own private space, data rules, and usage reports. None of it needs manual setup.
Protecto replaces a value with a stand-in that keeps the same format and meaning. Agents still read and understand the content, so the output stays accurate.
Adding a customer is an API call, not a deployment. Automation Anywhere integrated in days; after that, each new customer was a few lines of code.
Every decision is logged: what was found, how it was protected, who accessed it. Security reviewers could see exactly what was happening — and sign off.
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The results
Key achievements
Book a demo to see how Protecto finds and masks sensitive data before it reaches any AI model.
