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Search foundation models: embeddings, reranker, Reader API
Updated
Jina AI develops frontier search foundation models for enterprise search and retrieval-augmented generation. Its products include multimodal, multilingual embedding models, a reranker, the Reader API and a web search API. The company has presented 21 papers at conferences including EMNLP, SIGIR, ICLR and NeurIPS.
Developers call the APIs with an API key. Reader fetches a page, optionally runs JavaScript and extracts content by selector, then returns markdown or JSON. Embeddings and the reranker feed retrieval pipelines for RAG.
Developers building RAG, agents and search use Jina AI. Open source components are on GitHub and Hugging Face.
Jina offers a free tier with token limits, and an API key raises rate limits. Pricing is token-based, but specific rates were not shown on the pages reviewed.
Jina AI is compared with Reducto, Extend and Affinda. Reducto and Extend focus on document parsing, and Affinda on resume and document extraction.
Pricing Model
USAGE BASED
Starting Price
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Free version
| Feature | Free | API key |
|---|---|---|
| Free tokens with rate limits | , | |
| Higher rate limits | , | |
| Token-based pricing | , |
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Compliance Standards
SOC 2 Type II
EnterpriseISO 27001
EnterpriseGDPR Compliant
GlobalHIPAA
HealthcarePCI DSS
FinanceCCPA
PrivacyFedRAMP
GovernmentCSA STAR
CloudDeployment & Data
Data Residency Options
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Document parsing, extraction and classification API
Unstructured data platform for insurance
Agentic document parsing and extraction API for AI pipelines
No-code document intelligence for contracts and finance
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