Looking for Feedback & Collaborators: Semantic DLP for Enterprise AI

Hi everyone! 👋

I'm Mohammed Aswath, an AIML undergraduate . I've been building AI projects around industrial document intelligence (my previous project was AI-based P&ID digitization), and recently I've been exploring AI security.

I'm considering my next project around a problem that I believe is becoming increasingly important:

Title :

Semantic Data Loss Prevention (DLP) for AI Copilots and RAG Systems

Traditional DLP protects files, emails, and databases. Modern AI systems, however, convert enterprise documents into embeddings stored in vector databases and retrieve knowledge through semantic search. This creates a new risk where AI can unintentionally expose sensitive knowledge through retrieval or generated responses, even when file-level permissions are enforced.

Microsoft researchers have also highlighted this challenge in enterprise AI: https://arxiv.org/abs/2509.14608

https://arxiv.org/pdf/2509.14608

The idea is to build a security layer that enforces access control at the embedding, retrieval, and response generation stages, enabling enterprises to adopt AI more securely.

I'd really appreciate your thoughts:

Is this a meaningful problem statement?

Are there existing approaches or research I should explore?

If this problem interests you and you'd like to collaborate, feel free to comment or DM me.

Looking forward to your feedback!

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Looking for Feedback & Collaborators: Semantic DLP for Enterprise AI