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Qdrant - Vector Database

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Qdrant 1.17 - Relevance Feedback & Search Latency Improvements

Qdrant 1.17.0 is out! Let’s look at the main features for this version:

Relevance Feedback Query: Improve the quality of search results by incorporating information about their relevance.

Search Latency Improve...


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Relevance Feedback in Qdrant

A year ago, we dropped a statement-bomb in the “Relevance Feedback in Information Retrieval” article and then went silent.

We claimed that even though the information retrieval research field has proposed many useful mechanisms for increasing the relevance of se...


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How Bazaarvoice scaled AI-powered product insights with Qdrant

Turning billions of reviews into real-time, actionable intelligence

Bazaarvoice powers ratings and reviews across the global ecommerce ecosystem, connecting brands, retailers, and consumers through authentic product feedback. From brand-owned storefronts to major retailers, Bazaarvoice sources, verifies, and amplifies reviews at a scale few companies ever reach.

<...

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Sketch & Search: Google Deepmind x Qdrant x Freepik Hackathon Winners

Builders from around the world came together for Sketch & Search, a global hackathon powered by Google DeepMind, Freepik, and Qdrant, to explore the future of AI-driven creative pipelines.

Teams were challenged to go beyond single-prompt generation and build end-to-end systems combining generative models, visual creation, and vector search. Submissions showcased co...


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Two Approaches to Helping AI Agents Use Your API (And Why You Need Both)

AI coding agents fail in predictable ways when working with APIs. Two recent approaches from Mintlify and Armin Ronacher attack different failure modes. Understanding both reveals something useful about how agents should interact with developer tools.

Two Failure Modes

When an agent writes code against your API, it can fail because:

It doesn’t know wha...


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