AI Assistant for Cybersecurity: Performance Hacks

Developing dependable AI assistants—particularly in critical areas like cybersecurity—requires getting the retrieval layer of RAG systems right. Our research shows that even minor adjustments can trigger “retrieval drift,” gradually undermining performance.

This white paper explores how subtle issues, such as mismatched embedding wrappers or flawed similarity metrics, can compromise accuracy. More importantly, it provides practical solutions: in-depth evaluation techniques, detailed architecture diagrams, and actionable implementation guidance.

Don’t let hidden retrieval flaws erode the effectiveness of your AI assistants. Download the white paper and learn how to build a RAG system you can truly rely on.