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AI Search
Foundation Models
Natural Language Processing
Vector Search & RAG
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Overview
Jina AI builds search foundation models and APIs for developers of retrieval and AI search applications, now as part of Elastic. Its products include multimodal and multilingual embedding models, rerankers, small language models, the Reader API at r.jina.ai that converts any URL to LLM-ready markdown and a search endpoint at s.jina.ai. The company was founded in Berlin in 2020 by Han Xiao and co-founders, raised a $30 million Series A led by Canaan Partners in 2021 and was acquired by Elastic in October 2025 for $43.4 million.
News
jina-reranker-v3.5: An Efficient Listwise Reranker with Hybrid Attention and Self-Distillation
Abstract page for arXiv paper 2607.18152: jina-reranker-v3.5: An Efficient Listwise Reranker with Hybrid Attention and Self-Distillation
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jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers
Abstract page for arXiv paper 2605.08384: jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers
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jina-embeddings-v5-text: Task-Targeted Embedding Distillation
Abstract page for arXiv paper 2602.15547: jina-embeddings-v5-text: Task-Targeted Embedding Distillation
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jina-vlm: Small Multilingual Vision Language Model
Abstract page for arXiv paper 2512.04032: jina-vlm: Small Multilingual Vision Language Model
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Report
Elastic Completes Acquisition of Jina AI, a Leader in Frontier Models for Multimodal and Multilingual Search
Detailed price information for Elastic N.V. (ESTC-N) from The Globe and Mail including charting and trades.
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jina-reranker-v3: Last but Not Late Interaction for Listwise Document Reranking
Abstract page for arXiv paper 2509.25085: jina-reranker-v3: Last but Not Late Interaction for Listwise Document Reranking
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jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval
Abstract page for arXiv paper 2506.18902: jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval
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Report
Model Soup's Recipe for Embeddings
Boost robustness and performance with model soups: averaging weights. No extra cost, better results.
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Report
On the Size Bias of Text Embeddings and Its Impact in Search
Size bias refers to how the length of text inputs affects similarity, regardless of semantic relevance. It explains why search systems sometimes return long, barely-relevant documents instead of shorter, more precise matches to your query.
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Report
A Practical Guide to Implementing DeepSearch/DeepResearch
QPS out, depth in. DeepSearch is the new norm. Find answers through read-search-reason loops. Learn what it is and how to build it.
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Products
Reranker
Reranking models that reorder search results by relevance. Used on top of vector or keyword retrieval.
jina.ai
Embeddings
Multimodal and multilingual embedding models for vector search and RAG. Offered through an API and as open models.
jina.ai
Reader API
Converts a URL into clean markdown for grounding LLMs via r.jina.ai. A companion endpoint at s.jina.ai returns web search results in the same format.
jina.ai
People

Han Xiao
Co-founder, former CEO
Founded Jina AI in Berlin in 2020 and led it as CEO until the Elastic acquisition. Became VP of AI at Elastic after the deal closed.

Nan Wang
Co-founder
One of the four co-founders of Jina AI in 2020.

Bing He
Co-founder
One of the four co-founders of Jina AI in 2020.

Jiao Liu Authorizing
Managing Director
Names and roles come from public filings, company registers and the company's own site. Is this you? Correct or remove · How we handle this data
Offices
Where the company hires and what each office is for
Cities
1
Hiring now
0
Countries
1
Berlin
Germany
HQ
Financials
Total raised
$73.4M
Latest round
Acquired
Funding rounds
2
Investors
4
Key Investors
Elastic
Elastic is the NYSE-listed company behind Elasticsearch that acquired Jina AI in 2025.
elastic.co
GGV Capital
GGV Capital is a global venture capital firm investing in technology companies.
ggvc.com
Canaan Partners
Canaan Partners is a US early-stage venture capital firm that led Jina AI's Series A.
canaan.com
