Jina AI

Jina AI is a search foundation platform that provides the retrieval building blocks agents and RAG systems need, delivered as token based APIs behind a single key. Its core products are a Reader that converts any URL or PDF into clean, model ready markdown by prepending a host to the address, world class multimodal and multilingual embeddings, a reranker that reorders retrieved results by true relevance, plus DeepSearch, a classifier, a segmenter, and fine tuning. The reranker supports function calling and code search, the embedding models span text and images with long context, and the same API key and shared token pool work across every service. In October 2025 Jina AI was acquired by Elastic, and while the Reader, embedding, and reranker APIs and open weight models continue, the roadmap points toward tighter Elasticsearch integration over time.

For agent builders, Jina is the layer that grounds a model in current, real world information. A typical flow reads a page with Reader, stores it, embeds it for recall, retrieves a wide set from a vector database, then reranks narrow before handing clean context to a generator. Because the interfaces are API first and token metered, Jina fits naturally into automation flows built with n8n, Zapier, or LangChain, and models can run natively inside Elasticsearch or through the Model Context Protocol.

Pricing is based on total tokens processed, shared flexibly across all services. New keys include millions of free tokens with no card, embeddings run as low as two cents per million tokens, and token top ups are available in large bundles with Standard and Premium tiers that raise rate limits and add priority support and auto top up. Models can also be deployed through AWS and Azure marketplaces or, for Elastic customers, on premises under an Elastic license. Open weight models are released under a non commercial license, and Jina states it never trains on customer inputs or outputs.