Your AI Agents Need Data. But Should They See It? | LibreChat + Protecto
Can enterprises use powerful AI models with sensitive data without forcing everything into a self-hosted model?
That's the problem this demo explores.
In this session, we demonstrate Protecto Privacy Gateway integrated with LibreChat and show how sensitive enterprise data can be protected across AI chat, RAG, agents, MCP/tool calls, and long-running conversations.
Traditional masking can work for simple prompt → response workflows. But agentic AI introduces a much more complex environment: agents retrieve documents, call tools and APIs, work with RAG, maintain long conversation histories, and need specific sensitive information to complete certain actions.
The demo shows how Privacy Gateway works with Protecto Privacy Vault to:
Chapters:
00:00 — Why enterprises need an AI privacy layer
01:46 — Why Protecto built Privacy Gateway
02:50 — Why agentic AI changes the security problem
04:20 — Why traditional masking doesn't work for agents
06:36 — Why Protecto built the Gateway
07:09 — Privacy Vault vs Privacy Gateway
10:58 — LibreChat + Protecto demo setup
12:47 — Introducing the LibreChat integration
13:31 — Protecting sensitive data in AI chat
15:42 — Custom policies and model flexibility
17:48 — Protecting RAG and AI agents
19:08 — Protecting SharePoint RAG data
20:34 — How masked RAG works
21:06 — Consistent tokenization across prompts and RAG
23:44 — Building agents with protected data
24:15 — Using different AI models with sensitive data
25:38 — MCP and tool-call protection
27:19 — Protecting long conversations and context
29:27 — How to get started
The session also demonstrates a LibreChat + RAG + AI agent workflow, including a Policy Agent connected to SharePoint data, where retrieved content is masked before being provided to the model.
The goal isn't to replace the AI experience.
It's to add a privacy boundary around it.
Watch the full demo to see what happens behind the scenes when a user asks questions containing sensitive information, and how the Privacy Gateway protects the data while keeping the AI workflow usable.
🔗 Explore Protecto
Website: https://www.protecto.ai/
Protecto Privacy Gateway: https://www.protecto.ai/product/privacy-gateway-for-ai-chat/
Protecto on GitHub: https://github.com/ProtectoAi/protecto-librechat-gateway
💬 What do you think?
Would your organization use public AI models for sensitive enterprise workloads if the sensitive data could be protected before reaching the model?
And for AI agents:
Should sensitive data be masked everywhere or selectively revealed when a specific tool actually needs it?
Share your thoughts in the comments.
#aisecurity #LibreChat #agenticai #RAG #aiprivacy #sensitivedata #protectoai #enterpriseai #llmsecurity #mcp #dataprivacy