Qdrant B2B Case Studies & Customer Successes

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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! Powering the next generation of AI applications with advanced and high-performant vector similarity search technology.

Case Studies

Showing 13 Qdrant Customer Success Stories

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Dailymotion's Journey to Crafting the Ultimate Content-Driven Video Recommendation Engine with Qdrant Vector Database

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How Deutsche Telekom Built a Multi-Agent Enterprise Platform Leveraging Qdrant

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Using AI to Unlock Company Knowledge and Drive Employee Productivity

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HubSpot & Qdrant Scaling an Intelligent AI Assistant

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IrisAgent and Qdrant Redefining Customer Support with AI

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Transforming Wealth Management with AI-Driven Insights and Scalable Vector Search

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Kern AI & Qdrant Precision AI Solutions for Finance and Insurance

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How Vectors are the Future of Visual Search

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Empowering QA.tech’s Testing Agents with Real-Time Precision and Scale

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How Sprinklr Leverages Qdrant to Enhance AI-Driven Customer Experience Solutions

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How Tripadvisor Drives 2 to 3x More Revenue with Qdrant-Powered AI

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Visua and Qdrant Vector Search in Computer Vision

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Powering No-Code AI Agent Creation with Scalable Vector Search

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