> ## 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. # Jina AI > Connect Pinecone and Jina 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}
}
; Jina Embeddings leverage powerful models to generate high-quality text embeddings that can process inputs up to 8,000 tokens. Jina Embeddings are designed to be highly versatile, catering to both domain-specific use cases, such as e-commerce, and language-specific needs, including Chinese and German. By providing robust models and the expertise to fine-tune them for specific requirements, Jina AI empowers developers to enhance their search functionalities, improve natural language understanding, and drive more insightful data analysis. By integrating Pinecone with Jina, you can add knowledge to LLMs via retrieval augmented generation (RAG), greatly enhancing LLM ability for autonomous agents, chatbots, question-answering, and multi-agent systems.