What security problem does Cloaked AI solve for AI workflows?
Cloaked AI solves the problem that vector embeddings in AI workflows are not truly anonymized and can be inverted back to approximate the original sensitive data, creating a high risk of data loss in vector databases. It encrypts embeddings at the application layer before they leave the app, ensuring the vector database never sees plaintext while still allowing for nearest-neighbor search, hybrid queries, and metadata filters. This is described as fixing the 'dirty secret of RAG and vector search' where embeddings are recoverable copies of private data.
Who is the target audience for Cloaked AI?
Cloaked AI is for engineering teams building generative AI, vector search, and multi-tenant SaaS applications who need advanced encryption tools to protect sensitive data. It targets organizations that must comply with data privacy requirements and want to ship AI features while keeping their data encrypted, even in use. The product is categorized as a Developer & AI Platform tool.
What features and integrations does Cloaked AI offer?
Cloaked AI offers application-layer encryption for vector embeddings and metadata, preserving functionality for nearest-neighbor search, clustering, and classification while encrypting data. It is database-agnostic and works with major vector databases including Pinecone, Qdrant, Weaviate, Chroma, OpenSearch, Elasticsearch, pgvector, Milvus, LanceDB, and Redis. The SDK is open source on GitHub (AGPLv3) and plugs into the SaaS Shield platform for key management, audit trails, and multi-tenant functionality.
What is Cloaked AI used for and in what situations?
Cloaked AI is used to secure sensitive data within vector databases for AI workflows, including generative AI, vector search, and multi-tenant SaaS applications. It is applied in situations where organizations need to build AI features on protected data without compromising security, such as when using Pinecone, Qdrant, Weaviate, Chroma, or other vector databases. The product allows for encrypted semantic search and protects embeddings used for classification, clustering, and nearest-neighbor search.
What is Cloaked AI?
Cloaked AI is a commercial vector encryption product designed to secure sensitive data within vector databases used in AI workflows. It encrypts embeddings and metadata at the application layer, allowing them to remain useful for search and analysis while preventing the vector database from ever seeing plaintext data. The product is part of the IronCore Labs platform and is categorized as a Developer & AI Platform tool.
5 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.
