docs.dev vs Open

Point your coding agent at your repo and your docs; it opens a docs branch, your team reviews on the rendered page, publishing is a commit. Runs on your Cloudflare, no...

Open-source RAG security toolkit with prompt injection detection, PII protection, secrets scanning, and retrieval integrity checks.

About docs.dev

Point your coding agent at your repo and your docs; it opens a docs branch, your team reviews on the rendered page, publishing is a commit. Runs on your Cloudflare, no platform fee, no metered AI. Reviews, branches, and rollbacks come free, because it is just git. Your content in their database, and an export button you hope works when you leave. Writing AI is the agent you already have; reader-facing AI runs on your Workers AI.

About Open

Open-source RAG security toolkit with prompt injection detection, PII protection, secrets scanning, and retrieval integrity checks. AetherGuard AI is a unified zero-trust infrastructure for generative AI deployments, combining semantic security inspection, AI threat intelligence, cryptographic accountability, and hardware-rooted trusted execution into a single AI-native defense pipeline. Retrieval-Augmented Generation (RAG) has quickly become the standard architecture for enterprise AI applications. Much less attention is given to a fundamental question:. Traditional RAG pipelines assume that anything returned from a vector database is safe and trustworthy.