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title: Our story
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.
content: After exploring available options, including libraries like FAISS, it became clear that none of them met the requirements of features and scalability.
image:
alt: Qdrant Team
src: /img/about-us/team-1x.jpg
srcLarge: /img/about-us/team-2x.jpg
extraContent1: As a result, Andrey decided to develop his own vision for a production-ready vector search engine from scratch.
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.
extraImage1:
alt: Team
src: /img/about-us/team2-1x.jpg
srcLarge: /img/about-us/team2-2x.jpg
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.
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.
extraImage2:
alt: Team
src: /img/about-us/team3-1x.jpg
srcLarge: /img/about-us/team3-2x.jpg
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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---