April 19, 2023
Portfolio
Unusual

Why we led Qdrant’s $7.5M Seed round

Why we led Qdrant’s $7.5M Seed roundWhy we led Qdrant’s $7.5M Seed round
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Editor's note: 

We’re excited to announce our Seed investment in Qdrant, the open-source vector database poised to become a cornerstone of the new AI stack. We are incredibly optimistic about the potential for vector databases to transform the future of AI applications, but even more than that, we are inspired by Qdrant’s founders and team. In all of our work with AI/ML builders, we see the growing need for vector databases, and we believe Co-founders André Zayarni (CEO) and Andrey Vasnetsov (CTO) have the insight and technical expertise to realize this opportunity.


Why do vector databases matter?

Vector databases are a critical piece of infrastructure that power the most impactful modern machine learning systems:

  • Modern recommendation systems, like the ones that power social media feeds, rely on extremely high-performance similarity search – one of the core capabilities of vector databases.
  • Large language models (LLMs) heavily utilize “in-context learning,” where relevant information is presented to models to improve factual responses. Vector databases power the critical information retrieval infrastructure for these use cases.
  • Vector databases are the most commonly used backend for semantic search, providing a richer experience, particularly when searching over multi-modal assets.

Not only is Qdrant the most performant vector database, it’s also the easiest for organizations to set up, manage, and scale — which translates to higher velocity release cycles and lower costs for customers. The Qdrant team launched Qdrant Cloud in February 2023 and is serving more than 1,000 Qdrant clusters. Now they’re extending their offering with managed on-premise solutions for enterprise customers. CEO Andre Zayarni attributes much of the product’s success to their open-source community: “I cannot imagine how we could do what we’re doing without the community or being open-source and having the trust of engineers,” he says.

We encourage all AI builders to check out Qdrant — they’re offering a free-forever 1GB cluster, and the product is remarkable.

About Qdrant’s Co-founders, Andre Zayarni and Andrey Vasnetsov

Qdrant was built by two brilliant minds – Andrey learned Rust and worked in his spare time (while still working a full-time job) to complete the first version of the database. Andre is an incredible product and engineering leader who has been a driving force in ensuring Qdrant is the most user-friendly vector database on the market. Our team at Unusual is excited to have the opportunity to partner with this incredible founding team.

The team at Unusual believes that Qdrant will be a staple of the infrastructure stacks that power the next generation of AI applications. We are thrilled to partner with Andre and Andrey as they continue to build the best product and company in the market.

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All posts
April 19, 2023
Portfolio
Unusual

Why we led Qdrant’s $7.5M Seed round

Editor's note: 

We’re excited to announce our Seed investment in Qdrant, the open-source vector database poised to become a cornerstone of the new AI stack. We are incredibly optimistic about the potential for vector databases to transform the future of AI applications, but even more than that, we are inspired by Qdrant’s founders and team. In all of our work with AI/ML builders, we see the growing need for vector databases, and we believe Co-founders André Zayarni (CEO) and Andrey Vasnetsov (CTO) have the insight and technical expertise to realize this opportunity.


Why do vector databases matter?

Vector databases are a critical piece of infrastructure that power the most impactful modern machine learning systems:

  • Modern recommendation systems, like the ones that power social media feeds, rely on extremely high-performance similarity search – one of the core capabilities of vector databases.
  • Large language models (LLMs) heavily utilize “in-context learning,” where relevant information is presented to models to improve factual responses. Vector databases power the critical information retrieval infrastructure for these use cases.
  • Vector databases are the most commonly used backend for semantic search, providing a richer experience, particularly when searching over multi-modal assets.

Not only is Qdrant the most performant vector database, it’s also the easiest for organizations to set up, manage, and scale — which translates to higher velocity release cycles and lower costs for customers. The Qdrant team launched Qdrant Cloud in February 2023 and is serving more than 1,000 Qdrant clusters. Now they’re extending their offering with managed on-premise solutions for enterprise customers. CEO Andre Zayarni attributes much of the product’s success to their open-source community: “I cannot imagine how we could do what we’re doing without the community or being open-source and having the trust of engineers,” he says.

We encourage all AI builders to check out Qdrant — they’re offering a free-forever 1GB cluster, and the product is remarkable.

About Qdrant’s Co-founders, Andre Zayarni and Andrey Vasnetsov

Qdrant was built by two brilliant minds – Andrey learned Rust and worked in his spare time (while still working a full-time job) to complete the first version of the database. Andre is an incredible product and engineering leader who has been a driving force in ensuring Qdrant is the most user-friendly vector database on the market. Our team at Unusual is excited to have the opportunity to partner with this incredible founding team.

The team at Unusual believes that Qdrant will be a staple of the infrastructure stacks that power the next generation of AI applications. We are thrilled to partner with Andre and Andrey as they continue to build the best product and company in the market.

All posts

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

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