We Only Use Private AI. We're Safe.
Why private LLMs still pose a compliance and reputational risk
You hear this one a lot:
“Our models are private. We're not sending anything to ChatGPT. We're covered.”
That sounds good. In fact, it's a step in the right direction. Private LLMs absolutely reduce exposure. They keep your data out of third-party hands and off the public internet.
But that doesn't mean you're fully protected.
The Myth
“We've locked things down. Our AI runs privately. We're safe.”
This is one of those beliefs that sounds safe because it includes the word “private.” And to be fair, using internal models, enterprise APIs, or self-hosted tools is a big upgrade.
But it doesn't solve for the biggest risk: what your people put in.
The Reality
When someone says “private AI,” they usually mean one of three things:
- 1. A fully self-hosted model running on internal infrastructure
- 2. An enterprise-grade LLM hosted on a secure cloud (like Azure OpenAI or Claude API)
- 3. A paid version of a public tool with stronger controls (like ChatGPT Team or Enterprise)
All of these options are safer than public tools. They help ensure your data isn't used for training and stays more tightly controlled.
But none of them protect the inputs.
If someone submits personal data into a prompt—names, case details, employee concerns—it doesn't matter how secure the model is. That sensitive data still entered a system, still got processed, and still might be logged, stored, or output.
Private AI protects the backend. It doesn't protect the front door.
Where Things Go Wrong
Here's what we see over and over:
- • Teams relax because they're not using public tools
- • Prompts feel “safe” because they're inside the firewall
- • But users still submit sensitive content without review
The result? Accidental leaks. Prompt logs full of confidential info. No awareness until something goes sideways.
The Reputational Risk
Compliance is important. But so is perception.
Even if your tech stack checks every box, it won't matter if a prompt containing PII gets misused or exposed. Clients won't care if it was public or private. They'll care that it happened.
Headlines don't include disclaimers. They just say “data breach.”
What You Can Do About It
Using private AI is smart. But you still need to protect the prompt.
That's where PII Shield comes in.
It scans prompts before they ever reach the model. Whether it's hosted in your own cloud or coming from a secure API, we stop risky data at the source.
No retraining. No complicated setup. Just a simple check that runs quietly in the background.
Think of it as the missing first step. If you're already investing in private AI, this closes the loop.
Private AI is Safer. But It's Not Safe By Default.
Private infrastructure is great. But privacy still depends on what goes in.
Protect your model. But protect your inputs too.