Qdrant is a technology company which offers an open-source vector similarity search engine to developers and organizations. Their platform is designed to enable efficient similarity searches across large datasets, with the goal of supporting high-performance and scalable search applications. By providing tools for various use cases such as recommendation systems, image search, and semantic search, Qdrant aims to enhance the capabilities of AI-powered applications. This company was founded by André Zayarni and Andrey Vasnetsov in 2021 and is headquartered in Berlin, Germany.

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Qdrant Stock Price

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Price not yet available
Last Closed Trade 2
Close Date
xx/xx/xx
Last Closed Trade Price
$xx.xx
Last Funding Round (LFR)
Date
xx/xx/xx
Price per Share
$xx.xx

Qdrant Funding Rounds and Valuation

Funding History Chart
Funding Round Details
Funding Date Share Class Amount Raised Price per Share Post-Money Valuation Key Investors
Funding Round Details are not yet available for this company.

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Leadership & Board

Leadership

André Zayarni
Co-Founder & Chief Executive Officer
Andrey Vasnetsov
Co-Founder & Chief Technology Officer
Fabrizio Schmidt
Vice President of Engineering and Product
Manuel Meyer
Head of Growth
Karim Chester
Head of Sales
David Myriel
Director of Developer Relations
Bastian Hofmann
Director of Enterprise Solutions
Dominik Alberts
Finance Manager

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Qdrant News and Media Highlights

Qdrant Introduces BM42: Hybrid Search For Enhanced RAG

Qdrant, a leading provider of vector database solutions, has recently unveiled an innovative search technology called BM42. This new approach promises to revolutionize information retrieval, especially in AI applications that rely on retrieving data as a part of retrieval-augmented generation pipelines that provide context to the language models.

Qdrant launches first vector database as a managed hybrid cloud

Today’s complex, unstructured data — text, images, audio and video — are difficult for traditional databases to handle. They struggle with this complex, demanding data with large numbers of variables and features. Vector databases have emerged to handle this problem; they are specialized databases that can efficiently index, query and retrieve the high-dimensional data critical to building and running AI.

Open source vector database startup Qdrant raises $28M

Qdrant, the company behind the eponymous open source vector database, has raised $28 million in a Series A round of funding led by Spark Capital. Founded in 2021, Berlin-based Qdrant is seeking to capitalize on the burgeoning AI revolution, targeting developers with an open source vector search engine and database — an integral part of generative AI, which requires relationships be drawn between unstructured data (e.g. text, images or audio that isn’t labelled or otherwise organized), even when that data is “dynamic” within real-time applications.
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Updated on: Dec 22, 2024

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