Solving the data security challenge for AI builders

This post discusses the potential risks of using contextual data with large language models (LLMs) and demonstrates how HashiCorp Vault can integrate with Pinecone to tackle AI data security challenges. It highlights the complexity of securing retrieval-augmented generation (RAG) enhanced AI applications, as they fetch information from external sources to provide more accurate responses. The integration of diverse data sources increases the risk of data leakage and manipulation by malicious actors. To address these issues, HashiCorp Vault can be used to encrypt sensitive information before it is stored in Pinecone, ensuring that the data remains protected even if the vector database is compromised. The post also provides a step-by-step guide on how to integrate Vault into a RAG system using Pinecone and Terraform.