Enterprise AI Just Got Safer: Introducing GPTGuard 2.0

“How do I stop my data from leaking into a public LLM model?”
That single question derailed more AI projects than any technical challenge ever could.

When our customers first started experimenting with generative AI, they ran into a wall — fast. Not a technical one. A control one.

The single biggest concern we consistently heard from CIOs and CISOs wasn’t ransomware or zero-day exploits. It was public LLMs — specifically, the surge of ungoverned tools like ChatGPT spreading across teams.

In just two years, this explosion in usage led to the rise of shadow AI: unofficial tools being used across functions, with no oversight. Employees — knowingly or unknowingly — were feeding sensitive customer data, internal IP, even security details into external LLMs.

The only way IT leaders have been able to contain this risk? Ban them.
But blocking AI entirely isn’t a real strategy. It’s a competitive disadvantage.

That’s exactly why we built GPTGuard — to give enterprises a way to embrace GenAI safely. With real-time masking, file-level security, and deployment options that give CIOs and CISOs full control, GPTGuard enables secure usage of LLMs without ever exposing sensitive data to public models.

Let me show you how.

The Big Roadblock: Why Enterprises Are Still Nervous About AI

Let’s be honest — most enterprises aren’t afraid of AI itself. They’re afraid of what AI might see.

When employees type prompts into tools like ChatGPT or Claude, they’re not thinking about compliance. They’re thinking about speed. And without realizing it, they’re often pasting:

• Customer data (45% of leaks)
• Employee records (26%)
• Legal and financial info (15%)
• Even penetration test results, network configs, and incident reports (nearly 7%)

According to Harmonic’s Q4 2024 report, 8.5% of employee prompts to public AI tools contained sensitive information. Worse? 64% of those users were on free AI tiers — which means those prompts might be used for training.

This isn’t a minor slip-up. It’s a legal, compliance, and brand trust crisis waiting to happen.

Meet GPTGuard: Your AI Chat, Without the Data Risk

It’s your own private enterprise chat interface — built to look and feel like ChatGPT, but with guardrails baked in. Here’s what it does:

✅ Detects and masks sensitive data (PII, PHI, etc.) from both prompts and documents

✅ Prevents any raw sensitive data from reaching your LLM

✅ Unmasks the response seamlessly so your users get full clarity

✅ Works with any major LLM — OpenAI, Claude, Gemini, Llama, DeepSeek, you name it

✅ Lets you upload files and chat with internal docs via secure RAG

Most importantly, highest accuracy – our intelligent masking delivers highest response accuracy even with sensitive data masked 

The best part? It’s fast, flexible, and requires zero technical gymnastics. SaaS or on-prem, you choose.

Many organizations, such as banks in UAE, are restricted by data residency regulations that define where personal data can be stored and processed. GPTGuard on-premises gives them complete control and compliance.

Behind the Scenes: The Tech That Powers GPTGuard

GPTGuard runs on Protecto’s Privacy Vault API, which is purpose-built for enterprise-grade data security in AI workflows.

Here’s how it works:

• Sensitive Data Identification: Uses a blend of regex, algorithms, and proprietary AI models to find PII, PHI, and even custom sensitive terms tied to your org.
• Entropy-Based Tokenization: We don’t just mask — we preserve format, type, and structure so the LLM can still understand what’s going on.
• Semantic Tagging: Each token carries context (e.g., <PER>Token123</PER>) so LLMs maintain accuracy — no hallucinations, no broken replies.
• Highest Accuracy: Our PII scanning outperforms AWS Comprehend and Microsoft Presidio by a wide margin. Lower false positives, better recall (F1 Score of >0.97, the highest in the industry).

You don’t lose precision. You gain peace of mind.

Security Without Sacrificing Usability

One of the first things we asked ourselves while building GPTGuard was — can we make AI chat better, not just safer?

Turns out, yes.

Most enterprise teams don’t just want to ask a model generic questions — they want it to understand their business context. That means tapping into internal data: SOPs, contracts, support documents, architecture diagrams, even scanned PDFs.

But here’s the catch — uploading internal documents into a public AI tool? That’s a huge no-go. Most of those tools were never designed to handle sensitive enterprise data securely.

That’s where our HyperSearch RAG system comes in.

Why HyperSearch RAG? Because LLMs Don’t Know Your Business

Out of the box, even the best LLMs have no idea about your internal documentation. Retrieval-Augmented Generation (RAG) fixes that by retrieving relevant chunks from your own files and feeding them to the LLM at runtime.

We built HyperSearch RAG — a proprietary hybrid search engine that:

• Combines entity-aware and vector-based search for precision
• Supports millions of documents with low latency
• Surfaces the most accurate context, even for nuanced or domain-specific queries
  

When you ask a question, GPTGuard fetches the best answer from your documents — not just the internet. And you can see exactly where that answer came from.

How GPTGuard Keeps Your Internal Data Safe

Unlike most RAG setups that expose raw data to the model, GPTGuard masks it before it ever reaches the LLM. Here’s how we keep your data airtight:

✅ Sensitive data is masked at ingestion — both in files and user prompts

✅ OCR support for scanned PDFs and image files ensures nothing slips through

✅ Transparent source tracing shows what data was accessed and what was masked

You can even chat with both internal documents and public LLMs in a single flow — switching back and forth without compromising security.

Why Do Enterprises Need GPTGuard?

GPTGuard helps enterprises unlock the power of GenAI without risking data leaks or violating compliance. Whether you’re in finance, healthcare, or government, it gives you full control — including on-prem deployment — so your data stays protected, private, and productive.

What Makes GPTGuard Different?

Let’s call it like it is — there are a bunch of AI privacy wrappers out there. But most of them fall into two camps:

• ✅ They’re secure but kill LLM performance
• ✅ Or they’re usable but leave gaping compliance holes

GPTGuard bridges that gap. Here’s what sets us apart:

We’re not just adding “privacy” to check a box. We’re rebuilding AI adoption from the ground up — for real-world constraints.

Who Should Use GPTGuard?

GPTGuard is built for enterprise teams that need the speed of GenAI without compromising security. It’s ideal for:

• Organizations handling sensitive data like financial records, health information, or legal contracts — enabling safe AI use through real-time masking and on-prem deployment
• Companies that have banned public AI tools but still want to empower employees with a secure, private alternative; and
• Cross-functional teams that need fine-grained access control to ensure the right people see the right data — and nothing more.

AI You Can Actually Trust

Here’s the truth: You don’t need to ban AI. You just need the right guardrails.

GPTGuard gives you a way to unlock AI’s full potential — safely.
No sensitive data slipping into prompts. No surprises in LLM training. No loss in accuracy.

It’s not a sandbox. It’s production-ready AI, without the security headache.

Let’s Make Enterprise AI Safer — Together

Curious if GPTGuard fits into your stack?

Try it for free Or book a meeting. We’ll help you figure out how to move your GenAI roadmap forward — safely, smartly, and without compromise.