Titelbild von QdrantQdrant
Qdrant

Qdrant

Softwareentwicklung

Berlin, Berlin 59.324 Follower:innen

Composable high-performance vector search

Info

Powering the next generation of AI applications with advanced and high-performant vector similarity search technology. Qdrant is an open-source vector search engine. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more. Make the most of your Unstructured Data!

Website
https://qdrant.tech
Branche
Softwareentwicklung
Größe
51–200 Beschäftigte
Hauptsitz
Berlin, Berlin
Art
Privatunternehmen
Gegründet
2021
Spezialgebiete
Deep Tech, Search Engine, Open-Source, Vector Search, Rust, Vector Search Engine, Vector Similarity, Artificial Intelligence , Machine Learning und Vector Database

Produkte

Orte

Beschäftigte von Qdrant

Updates

  • Qdrant hat dies direkt geteilt

    I'm a big science fiction fan, and for me, who started reading sci-fi books in the previous century, we are now crossing the border where those science fiction stories about the future become reality. Last week, I watched Yann LeCun's recent interview, where he discussed world models and where AI is heading, and it inspired me to think about the role of memory and information retrieval in this context. In parallel, completely independently, one of our engineers made a simple experiment with Qdrant and V-JEPA 2. What a coincidence! Or not... In any case, I've tried to put my thoughts into a content piece. Here it is: "Memories about the Future". Main theoretical thesis: If the next generation of AI thinks and learns in vectors, its memory should probably be a vector store. The most interesting move is what I call memories about the future: encode the present, roll it forward to imagine where things are heading, then retrieve the past experiences most relevant to that predicted state. Not "what's like now," but "what's like where this is going." That unlocks episodic memory, reusable skill libraries, and novelty detection for safety — all as similarity queries against a memory bank. We spent years building vector search to answer "what is". The work ahead is answering what could happen.

  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Please join us in welcoming Lakhan Samani and Vivek B. to Qdrant! 🇮🇳 Both joining from India, they bring deep experience across software engineering, AI systems, cloud infrastructure, and open source. Lakhan Samani joins as a Senior Software Engineer from Vadodara, Gujarat. With 10+ years of experience, he’s built developer tools, cloud-native systems, and open-source projects, including Authorizer.dev. His interests span distributed systems, software architecture, open source, and technical education. Vivek B. joins as a Senior Support Engineer from Hyderabad. An AI Engineer with 7+ years of experience, he has worked across machine learning, agentic AI, and enterprise software. Outside of work, he’s a passionate cricket player who brings the same energy and competitive mindset to engineering challenges. We’re excited to have them onboard as we continue building the future of vector search and AI infrastructure 🙌 #Qdrant #VectorSearch #AIEngineering #OpenSource

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Most in-car media systems still expect you to search with keywords. But when you’re driving, you don’t think in keywords - you think in moods, vibes, and intent. This project by Sarvesh Talele, built with Qdrant Edge, creates a fully local AI-powered media discovery system that lets users search music semantically through voice, text, and mood-based queries. What’s interesting: → Local voice transcription with Whisper → Semantic retrieval with vector embeddings → On-device vector search using Qdrant Edge → No cloud dependency required A great example of how vector search can power privacy-first, real-time experiences directly on-device. Read here: https://lnkd.in/gT8zzW9e #Qdrant #VectorSearch #SemanticSearch #EdgeAI #AIEngineering

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Tweaking chunk sizes and running a few demo queries is not an evaluation strategy. Laurie Voss (Head of DevRel, Arize AI) is coming to Vector Space Day on June 11 to replace vibes with measurement: the retrieval metrics that matter, golden datasets that survive contact with reality, and how to wire evals into CI so you find out about regressions before your customers do. If you’re building something novel in vector search, AI memory, context engineering, or retrieval infra, check out Vector Space Day on June 11 at The Midway: https://luma.com/vsd-sf

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Berlin folks 🇩🇪 Join us for an afternoon workshop on Multimodal Search with Qdrant. We’ll be at Merantix AI Campus working with Gemini's newest multimodal embedding model, to process audio and text data from Benzinga and supported by AskNews: https://luma.com/shfil13j And we’re not stopping there - later the same day, we’re also hosting our Vector Space Meetup: Retrieval in the Age of Agents at the same location! Both events are free to attend; reserve your spot today. Meetup link: https://lnkd.in/dfRK3w-9 See you in Berlin 🙌

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    About 90% of enterprise data is unstructured, and most of it lives in documents. PDFs, spreadsheets, Word files, the stuff that runs businesses. Preston Carlson from LlamaIndex is coming to Vector Space Day to talk about why even frontier models struggle with real-world documents, and what better OCR and agent harnesses actually unlock. Vector Space Day is a full-day conference for engineers building the next generation of retrieval systems. Get your ticket for June 11 at The Midway, SF: https://luma.com/vsd-sf

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  • Qdrant hat dies direkt geteilt

    Unternehmensseite für McKinsey France anzeigen

    32.148 Follower:innen

    👏📢 Félicitations aux 3 lauréats du VivaTech Startup Challenge organisé par McKinsey en collaboration avec France Deeptech, visant à identifier la prochaine génération de licornes et de décacornes « Made in Europe » : 🌟Beyond Aero, dans la catégorie « Décarbonation ». Cette startup toulousaine est spécialisée dans l’aviation durable avec pour objectif de développer un avion à propulsion hydrogène ✈️ 🌟Qdrant, dans la catégorie « IA et robotique ». Ce moteur de recherche vectorielle nouvelle génération alimente les couches de recherche et de mémoire des applications d’IA 🤖   🌟Surgitec Robotics, dans la catégorie « Women in DeepTech ». Cette startup, qui développe une plateforme robotique nouvelle génération pour la chirurgie des tissus durs (cerveau, rachis, orthopédie, ORL) a pour mission de rendre la robotique chirurgicale accessible à tous les établissements de santé🏥 Trois lauréats qui illustrent le dynamisme de l’écosystème DeepTech européen et la capacité de l’innovation à transformer durablement nos industries 🚀 #VivaTech #Innovation #DeepTech #Aviation #Hydrogen #Sustainability #WomenInTech #HealthTech #ArtificialIntelligence #Entrepreneurship #Scaleups

  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    We’re hosting Vector Space Meetup: Retrieval in the Age of Agents on June 11. RAG is the architectural foundation of production AI, and retrieval has fundamentally changed over time. Agents don’t just retrieve anymore - they decide when to search, what to search for, and whether results are good enough to act on. We’re gathering builders shaping this shift: cognee, n8n, deepset, makers of Haystack, and LlamaIndex for a panel driven entirely by YOUR questions. You’ll also hear from Qdrant’s Co-Founder & CTO, Andrey Vasnetsov, who will join for open discussions and networking with attendees. Join us! Register (approval required): https://lnkd.in/dfRK3w-9

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Please join us in welcoming David Berscheid and Pedro Nakano Tramontin to Qdrant 🚀 David joins as a Partner Account Manager from Berlin 🇩🇪, bringing years of experience across AI consulting, partnerships, GTM, and machine learning. After working closely with AI applications and enterprise solutions, he’s now excited to dive deeper into the data infrastructure powering modern AI systems and help build strong, meaningful partnerships around Qdrant. Pedro joins as a Staff Software Engineer based in Berlin. With a background spanning startups, telecom, and banking, he brings deep engineering and technical leadership experience - along with a strong passion for AI systems, security, and challenging engineering problems. Excited to have both of them onboard as we continue building the future of vector search and AI infrastructure 🙌 #Qdrant #VectorSearch #AIEngineering #MachineLearning

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  • Unternehmensseite für Qdrant anzeigen

    59.324 Follower:innen

    Building an AI agent is one thing. Building one that's intelligent, reliable, and actually ready for an enterprise environment is a different problem entirely. Gabriel Lebow from Vultr is coming to Vector Space Day to frame the key architectural ideas behind production-ready agentic AI: how scalable systems support context-aware reasoning, handle real-time decision-making, and hold up when the stakes are real. Get your ticket at https://luma.com/vsd-sf

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Finanzierung

Qdrant Insgesamt 3 Finanzierungsrunden

Letzte Runde

Serie A

28.000.000,00 $

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