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22 lines
1.6 KiB
Markdown
22 lines
1.6 KiB
Markdown
---
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title: Our story
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subtitle: In 2021, André Zayarni and Andrey Vasnetsov collaborated on a project aimed at leveraging vector similarity search to build a matching engine for unstructured data objects.
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content: After exploring available options, including libraries like FAISS, it became clear that none of them met the requirements of features and scalability.
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image:
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alt: Qdrant Team
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src: /img/about-us/team-1x.jpg
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srcLarge: /img/about-us/team-2x.jpg
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extraContent1: As a result, Andrey decided to develop his own vision for a production-ready vector search engine from scratch.<br/><br/>The first version was published on GitHub, quickly attracting significant interest from developers. The overwhelming feedback and questions from developers and startups confirmed that there was a shared need for such a tool.
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extraImage1:
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alt: Team
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src: /img/about-us/team2-1x.jpg
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srcLarge: /img/about-us/team2-2x.jpg
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extraContent2: As the project gained traction, the decision was made to formally establish Qdrant and continue developing the vector search engine into its current form.<br/><br/>Today, Qdrant is the backbone of the most ambitious AI applications, powering everything from groundbreaking startups to enterprise-scale deployments with the best open-source vector database and enterprise-ready solutions.
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extraImage2:
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alt: Team
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src: /img/about-us/team3-1x.jpg
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srcLarge: /img/about-us/team3-2x.jpg
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subContent: "Our team has grown to 75+ experts across 20+ countries, but our mission remains unchanged: building the most scalable, high-performance vector search engine to fuel the future of AI and machine learning."
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sitemapExclude: true
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---
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