Building Secure Agentic AI Workflows & Vector Integrations

## The Rise of Agentic AI Large Language Models have evolved from passive text generators into active agents capable of calling APIs, querying databases, and executing code. However, this autonomy introduces significant security surface areas. ## Vector Database Security Vector embeddings store semantic knowledge for retrieval-augmented generation (RAG). Ensuring proper access controls and data isolation prevents unauthorized retrieval of sensitive enterprise data. ## Mitigating Injection Risks Prompt injection remains a primary vector of attack. By isolating execution environments and enforcing strict schema validation on tool outputs, developers can build resilient AI workflows.