Agents need vector search more than RAG ever did

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...
Opinion
Database Trends and ApplicationsOpinion

Qdrant Receives $50M to Build Out a Vector Search Engine that AI Demands

Qdrant, the open-source vector search engine built in Rust for production workloads, announced it has secured $50 million in Series B funding will enable composable vector search as core ...

Qdrant raises $50M to bring flexible vector search to production AI systems

Open-source vector database startup Qdrant Solutions GmbH today announced it has raised $50 million in early-stage funding to pave the way for smarter and more reactive artificial intelligence apps.
Tech.eu

Qdrant closes $50M Series B to expand vector search infrastructure

Qdrant develops a vector search engine designed for production AI systems, enabling teams to configure retrieval, ranking, ...
Nature

Alphafold hits 'next level': the AI tool now predicts protein pairing

The database of 200 million protein-structure predictions now includes protein complexes, adding new biological relevance.
InfoQ

DoorDash Builds DashCLIP to Align Images, Text, and Queries for Semantic Search Using 32M Labels

DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared ...
InfoQ

QCon London 2026: Reliable Retrieval for Production AI Systems

At QCon London 2026, Lan Chu, AI Tech Lead at Rabobank, shared lessons from deploying a production AI search system used internally by more than 300 users across 10,000 documents. Her experience shows ...