Jina AI is a search-focused AI platform that develops infrastructure for retrieval, embeddings, reranking, and web content extraction. It provides APIs, open models, and developer tools that help companies build search systems, retrieval-augmented generation (RAG) pipelines, and AI agent workflows. Founded in 2020 by Han Xiao, the company focuses on what it calls “search foundation” models and infrastructure.

The platform is widely known for products such as Jina Reader, Embeddings, and Reranker APIs. Jina Reader converts webpages into LLM-friendly formats by prepending r.jina.ai to URLs, enabling AI systems to access clean web content without complex scraping pipelines. Jina also provides search endpoints (s.jina.ai) and MCP integrations for AI agent systems.

A major focus of Jina AI is retrieval infrastructure for modern AI systems. Its embedding models support multilingual and multimodal retrieval across text and images, while rerankers improve search relevance in RAG systems and enterprise search workflows. The company publishes open research and models covering embeddings, reranking, long-context retrieval, multimodal search, and retrieval optimization techniques such as “late chunking.”

Jina AI also develops “DeepSearch,” an agentic research system that combines iterative web search, reading, and reasoning. Unlike standard RAG systems that perform a single retrieval pass, DeepSearch operates as an autonomous agent capable of multiple search and reasoning cycles before generating an answer.

The company’s models are used in enterprise search, ecommerce discovery, finance, consulting, media archives, and AI agent systems. Major AI and software companies use Jina’s APIs and models for crawling, semantic retrieval, and grounding large language models with current information.

Jina AI originally started as an open-source neural search framework before evolving into a broader search AI platform. Over time, the ecosystem expanded from multimodal search infrastructure into embedding models, retrieval tooling, and APIs used across modern LLM applications.

In 2025, Jina AI was acquired by Elastic, integrating its retrieval and search technology into Elastic’s broader AI and enterprise search ecosystem.

Key features include:

• Embedding models for multilingual and multimodal retrieval
• Reranker APIs for improving search relevance
• Jina Reader for converting webpages into LLM-ready text
• Search APIs for web retrieval and grounding
• DeepSearch agentic search and reasoning system
• Long-context retrieval and embedding support
• Open research publications and open-source models
• MCP server support for AI agent integration
• APIs for enterprise search and RAG pipelines

Common use cases include:

• Building retrieval-augmented generation (RAG) systems
• Enterprise semantic search and document retrieval
• AI agents that browse and read the web
• Ecommerce search and recommendation systems
• Multilingual and multimodal search applications
• Knowledge retrieval for LLM grounding and context injection

Jina AI is positioned as a foundational infrastructure provider for AI search and retrieval systems, focusing on high-quality retrieval, grounding, and agent-compatible search tooling for modern AI applications.