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 ...

The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

Vector database pioneer Pinecone recognizes this and is pivoting to meet the specific needs of agentic AI. The company today announced Nexus, which it positions as a knowledge eng ...
VentureBeat

Vector database company Qdrant wants RAG to be more cost-effective

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...
techtimes

How RAG and Vector Databases Improve LLMs

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...
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 ...
Business Wire

KIOXIA AiSAQ™ Software Advances AI RAG with New Version of Vector Search Library

TOKYO--(BUSINESS WIRE)--In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives ...

Beyond RAG: Why every AI search platform is now agentic and what that means for your content

AI search has outgrown simple RAG. Learn how today’s hidden AI retrieval systems decide whether your content gets surfaced or ...
dbta

Augmenting Applications with Vector Search and RAG

AI is undoubtedly a formidable capability that poses to bring any enterprise application to the next level. Offering significant benefits for both the consumer and the developer alike, technologies ...

Why Data, Not Models, Determines AI Success

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations prepare, manage, and move their data. AI-ready data platforms, vector databases ...
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 ...
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 ...