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 ...
ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
SiliconANGLE

RAG data preparation startup Vectorize launches with $3.6M in seed funding

Data integration startup Vectorize AI Inc. says its software is ready to play a critical role in the world of artificial intelligence after closing on a $3.6 million seed funding round today. The ...
VentureBeat

Vectorize debuts agentic RAG platform for real time enterprise data

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now While vector databases are now increasingly ...
CRN

Infinidat Introduces RAG AI Data Services

‘We work with [customers’ file data] to accelerate the process of learning and help avoid hallucination. We are targeting on-prem data. So this is not designed to go search the web or anything. That’s ...
Computer Weekly

RAG AI: ‘Do it yourself,’ says NYC data scientist

Organisations should build their own generative artificial intelligence-based (GenAI-based) on retrieval augmented generation (RAG) with open source products such as DeepSeek and Llama. This is ...
InfoWorld

MongoDB releases mongot source code to boost RAG and AI workloads

MongoDB has released the source code of mongot, the engine that powers MongoDB Search and Vector Search, under the Server Side Public License. Analysts say the move would help developers of the ...

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.
Visual Studio Magazine

Empowering AI Applications with Vector Search in SQL Server and Azure Cosmos DB

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...
dbta

Context Engineering for AI-Readiness: Enterprise RAG Architectures and Vector Databases

Today's enterprises need effective retrieval-augmented generation that extends existing data architectures without replacing current investments. As organizations face challenges in scaling RAG ...
InfoWorld

Teradata adds Enterprise Vector Store to augment RAG

Teradata’s partnership with Nvidia will allow developers to fine-tune NeMo Retriever microservices with custom models to build document ingestion and RAG applications. Teradata is adding vector ...