How OpenTable Reinvented Restaurant Discovery with Qdrant
Daniel Azoulai
September 02, 2025
Balancing Relevance and Diversity with MMR Search
Thierry Damiba
September 04, 2025
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Qdrant Blog
How Fieldy AI Achieved Reliable AI Memory with Qdrant
Discover how Fieldy AI built a fault-tolerant AI memory platform with Qdrant, achieving 100% reliable real-time recall, seamless hybrid search, and significant cost savings at scale.
Daniel Azoulai
September 04, 2025
How PortfolioMind Delivered Real-Time Crypto Intelligence with Qdrant
Discover how PortfolioMind achieved significant reductions in latency and boosts in engagement by modeling real-time user intent with Qdrant.
Daniel Azoulai
July 31, 2025
Qdrant Edge: Vector Search for Embedded AI
Private Beta launching for Qdrant Edge - lightweight, embedded vector search engine designed to run on local hardware with limited persistent background threads, network access, or centralized coordination.
Qdrant
July 29, 2025
Qdrant for Research: The Story Behind ETH & Stanford’s MIRIAD Dataset
Discover how Qdrant contributed to ETH & Stanford researchers’ mission to advance the development of AI in medicine.
Evgeniya Sukhodolskaya & Daniel Azoulai
July 23, 2025
Qdrant joins AI Agent category on AWS Marketplace to accelerate Agentic AI development
Qdrant is now available in the new AWS Marketplace AI Agents and Tools category.
Qdrant
July 16, 2025
How &AI scaled global legal retrieval with Qdrant
Discover how &AI scaled to over a billion vectors and 250B+ tokens using Qdrant Cloud — enabling their AI patent agent to deliver verifiable, high-value results for litigators.
Daniel Azoulai
July 15, 2025
Introducing Qdrant Cloud Inference
Learn how to generate embeddings natively in Qdrant Cloud
Daniel Azoulai
July 15, 2025
Announcing Vector Space Day 2025 in Berlin
From building scalable RAG pipelines to enabling real-time AI memory and next-gen context engineering, we’re covering the full spectrum of modern vector-native search.
Qdrant
July 14, 2025
How Pento modeled aesthetic taste with Qdrant
Discover how Pento used Qdrant’s recommendation API and multivector support to model aesthetic preferences and power a taste-based discovery engine.
Daniel Azoulai
July 14, 2025
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