From Vector Databases to Knowledge Engines: The Next Layer of AI

AI agents have become the primary users of data systems, yet existing vector databases remain designed for human interaction, causing inefficient "brute force" retrieval loops and excessive token consumption. Pinecone CEO Ash Ashutosh introduces Nexus, a knowledge engine that shifts reasoning closer to the data source to function as a context compiler. By curating data specifically for agent tasks, Nexus improves task completion rates from below 50% to over 90% while reducing token usage by up to 90% and lowering latency to under 500 milliseconds. This evolution includes the development of NoQL, a new query language designed to standardize how agents interact with knowledge engines. By offloading specialized retrieval functions from large language models to dedicated infrastructure, this approach enhances trust, explainability, and economic efficiency in enterprise AI deployments.