We Raised $50M to Build Composable Vector Search as Core Infrastructure
Andre Zayarni
March 12, 2026

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

Discover how Alhena AI replaced multiple vector backends with Qdrant to deliver fast, accurate responses in customer-facing AI agents—and why hybrid search, filtering, and boosting were critical to success.
Daniel Azoulai
July 10, 2025

Discover how GoodData replaced brittle LLM prompts with a scalable RAG pipeline powered by Qdrant, reducing latency and enabling real-time AI analytics.
Daniel Azoulai
July 09, 2025

A Qdrant Star shares her hard-won lessons from her extensive open-source building
Clelia Astra Bertelli & Evgeniya Sukhodolskaya
July 09, 2025

Discover how Frankfurter Allgemeine Zeitung (FAZ) used Qdrant to build a metadata-rich semantic search engine that transforms archival journalism into an AI-powered research tool—with sub-second latency and over 60 fields of structured filtering.
Manuel Meyer
July 03, 2025

Discover how Lettria combined Qdrant and Neo4j to overcome the accuracy limitations of traditional vector-only RAG systems, significantly boosting precision, explainability, and performance in regulated industries like pharma, legal, and aerospace.
Daniel Azoulai
June 17, 2025

Migrate data across clusters, regions, from open source to cloud, and more with just one command.
Qdrant
June 16, 2025

Discover how Lawme accelerated legal automation and improved compliance by moving to Qdrant's hybrid vector search solution.
Daniel Azoulai
June 11, 2025

This guide explores critical architectural decisions for LegalTech builders using Qdrant, covering accuracy, hybrid search, reranking, score boosting, quantization, and enterprise scaling needs.
Daniel Azoulai
June 10, 2025
