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nastyapashandtrean
21776375a9
* Add Partnerspage * fix * fix padding * tablet get-started-small update * Add Customers page * incorparated site-header partial * fix * Add community page (#886) * Add community page * site-header partial on the comunity page --------- Co-authored-by: trean <trean.mi@gmail.com> * Add Brand-Resources and Subscribe pages (#930) * add Brand resources page * add Subscribe page * Add Qdrant for startups page (#934) * Add Qdrant for startups page * improve accordion and link to the form * fix * Add Stars page (#890) * Add Stars page * site-header partial on the stars page * overlay z-index fix --------- Co-authored-by: trean <trean.mi@gmail.com> * new pages content update and accompanying css and html changes (#943) * new pages content update and accompanying css and html changes * format, removed comment, fix * fixes * subscribe page hubspot form (#946) * brand resources content (#947) * Stars page content (#945) * stars page content update * stars images format, replaced stars hero image * uncommented stars menu link * update stats: github stars and discord members number * photo * stars content upd * stars list update * Startup program content (#961) * startup program hubspot form * form fixes * another form, some fixes * content upd * stars * temp build options for the startups program page --------- Co-authored-by: trean <trean.mi@gmail.com>
107 lines
4.2 KiB
Markdown
107 lines
4.2 KiB
Markdown
---
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title: Vector Space Wall
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link:
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url: https://testimonial.to/qdrant/all
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text: Submit Your Testimonial
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testimonials:
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- id: 0
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name: Jonathan Eisenzopf
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position: Chief Strategy and Research Officer at Talkmap
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avatar:
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src: /img/customers/jonathan-eisenzopf.svg
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alt: Avatar
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text: “With Qdrant, we found the missing piece to develop our own provider independent multimodal generative AI platform on enterprise scale.”
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- id: 1
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name: Angel Luis Almaraz Sánchez
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position: Full Stack | DevOps
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avatar:
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src: /img/customers/angel-luis-almaraz-sanchez.svg
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alt: Avatar
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text: Thank you, great work, Qdrant is my favorite option for similarity search.
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- id: 2
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name: Shubham Krishna
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position: ML Engineer @ ML6
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avatar:
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src: /img/customers/shubham-krishna.svg
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alt: Avatar
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text: Go ahead and checkout Qdrant. I plan to build a movie retrieval search where you can ask anything regarding a movie based on the vector embeddings generated by a LLM. It can also be used for getting recommendations.
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- id: 3
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name: Kwok Hing LEON
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position: Data Science
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avatar:
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src: /img/customers/kwok-hing-leon.svg
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alt: Avatar
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text: Check out qdrant for improving searches. Bye to non-semantic KM engines.
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- id: 4
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name: Ankur S
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position: Building
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avatar:
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src: /img/customers/ankur-s.svg
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alt: Avatar
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text: Quadrant is a great vector database. There is a real sense of thought behind the api!
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- id: 5
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name: Yasin Salimibeni View Yasin Salimibeni’s profile
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position: AI Evangelist | Generative AI Product Designer | Entrepreneur | Mentor
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avatar:
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src: /img/customers/yasin-salimibeni-view-yasin-salimibeni.svg
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alt: Avatar
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text: Great work. I just started testing Qdrant Azure and I was impressed by the efficiency and speed. Being deploy-ready on large cloud providers is a great plus. Way to go!
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- id: 6
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name: Marcel Coetzee
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position: Data and AI Plumber
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avatar:
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src: /img/customers/marcel-coetzee.svg
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alt: Avatar
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text: Using Qdrant as a blazing fact vector store for a stealth project of mine. It offers fantasic functionality for semantic search ✨
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- id: 7
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name: Andrew Rove
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position: Principal Software Engineer
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avatar:
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src: /img/customers/andrew-rove.svg
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alt: Avatar
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text: We have been using Qdrant in production now for over 6 months to store vectors for cosine similarity search and it is way more stable and faster than our old ElasticSearch vector index.<br/><br/>No merging segments, no red indexes at random times. It just works and was super easy to deploy via docker to our cluster.<br/><br/>It’s faster, cheaper to host, and more stable, and open source to boot!
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- id: 8
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name: Josh Lloyd
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position: ML Engineer
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avatar:
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src: /img/customers/josh-lloyd.svg
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alt: Avatar
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text: I'm using Qdrant to search through thousands of documents to find similar text phrases for question answering. Qdrant's awesome filtering allows me to slice along metadata while I'm at it! 🚀 and it's fast ⏩🔥
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- id: 9
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name: Leonard Püttmann
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position: data scientist
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avatar:
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src: /img/customers/leonard-puttmann.svg
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alt: Avatar
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text: Amidst the hype around vector databases, Qdrant is by far my favorite one. It's super fast (written in Rust) and open-source! At Kern AI we use Qdrant for fast document retrieval and to do quick similarity search for text data.
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- id: 10
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name: Stanislas Polu
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position: Software Engineer & Co-Founder, Dust
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avatar:
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src: /img/customers/stanislas-polu.svg
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alt: Avatar
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text: Qdrant's the best. By. Far.
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- id: 11
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name: Sivesh Sukumar
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position: Investor at Balderton
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avatar:
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src: /img/customers/sivesh-sukumar.svg
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alt: Avatar
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text: We're using Qdrant to help segment and source Europe's next wave of extraordinary companies!
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- id: 12
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name: Saksham Gupta
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position: AI Governance Machine Learning Engineer
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avatar:
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src: /img/customers/saksham-gupta.svg
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alt: Avatar
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text: Looking forward to using Qdrant vector similarity search in the clinical trial space! OpenAI Embeddings + Qdrant = Match made in heaven!
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- id: 12
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name: Rishav Dash
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position: Data Scientist
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avatar:
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src: /img/customers/rishav-dash.svg
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alt: Avatar
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text: awesome stuff 🔥
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sitemapExclude: true
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---
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