Could Your Developers Accidentally Leak Confidential Data to a Large Language Model?

At Resource Stack, we work with teams handling sensitive data across industries—from financial and health records to PII. As AI tools like ChatGPT and Gemini become part of daily workflows, a new risk has emerged: unintentional data exposure. It’s not negligence—it’s convenience:

  • A developer pastes code into an AI tool to debug.
  • An analyst shares a dataset to generate insights.
  • A team member drafts a client email with sensitive context.
How would you know if confidential data was leaked?

That question led us to Actifile, a modern Data Loss Prevention (DLP) solution built for today’s workflows. Here’s what stood out:

  • Real-time visibility into data movement 
  • Risk scoring based on file sensitivity
  • Monitoring of interactions with LLM endpoints
  • Audit trails that help guide safe AI usage 

We didn’t want to block innovation—we wanted to secure it. Actifile helped us do just that.

🔍 Key takeaway: AI tools are here to stay. The real challenge is ensuring your team uses them responsibly.

If you’re curious about how to protect your data in an AI-driven world, let’s talk.

📞 Schedule your free assessment today 
Email: info@resourcestack.com