> ## Documentation Index > Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt > Use this file to discover all available pages before exploring further. # Instill AI > Connect Pinecone and Instill AI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure. export const PrimarySecondaryCTA = ({primaryLabel, primaryHref, primaryTarget, secondaryLabel, secondaryHref, secondaryTarget}) =>
{primaryLabel && primaryHref &&
{primaryLabel}
} {secondaryLabel && secondaryHref &&
{secondaryLabel}
}
; Instill AI specializes in developing cutting-edge solutions for data, models, and pipeline orchestration. Their flagship source-available product, Instill Core, is a no-code/low-code platform designed to facilitate the development, deployment, and management of AI workflows. By simplifying the integration of various AI models and data sources, they enable businesses to harness the power of AI without requiring extensive technical expertise. Their solutions cater to a wide range of applications, from predictive analytics and autonomous AI agents to enterprise private knowledge bases, AI assistants, and beyond. The Pinecone integration with Instill allows developers to incorporate its API for vector upsert and query tasks into AI pipelines. Developers configure their Pinecone component within Instill Core by providing the necessary API key and base URL. They can then perform tasks such as querying vector similarities to retrieve the most relevant results, complete with metadata and similarity scores, or upserting new vector data to keep their datasets up-to-date. This integration enables the addition of knowledge to LLMs via Retrieval Augmented Generation (RAG), significantly enhancing the capabilities of autonomous agents, chatbots, question-answering systems, and multi-agent systems.