As part of NIST-CSF, we were required to have a DLP (Data Loss Prevention) software. We did a POC and compared Strac with other competitors like NetSkope. Strac was hands down a) very easy to setup b) once it was setup, we could see the actual findings and alerts for it, c) very responsive support - their engineering team actively listens to any feedback and responds to all issues. We leverage the major SaaS integrations and also their AI DLP solution which protects us from sharing sensitive data over ChatGPT, Google Gemini, Anthropic Claude, etc. Their dashboard and UX is pretty straightforward and gets our job done.

Our support team was looking for ways to offer a more robust omnichannel experience for customers without compliance risk. We get all kinds of sensitive information as we are in financial space - SSNs, card numbers, etc. When came across Strac, it was one of the easiest security tools I’ve seen. It was simple, easy to understand and use, and more importantly - it actually worked. Their machine learning models were accurate, did the right detection and even redaction when needed. The pricing is affordable and the customer service is readily available whenever we have a question. Implementation was a breeze and we were even able to set up SSO with Azure. I highly recommend Strac for your data discovery and DLP (Data Loss Prevention) needs.

We receive sensitive data in our customer support tool. Sensitive data is in our chat messages and also in audio recordings we receive from customers. For security and compliance reasons, we wanted a solution that could identify sensitive data and remove it from our customer support app. Strac solved that problem for us with their highly accurate machine learning and OCR (Optical Character Recognition) software. After weeks of researching, Strac was the only solution I could find on the market that identifies sensitive data in audio recordings. It was literally a 15 min onboarding. We did a quick demo with them and saw instant value. Very easy to use, easy to integrate, and accurate.