Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private ...
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 ...
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 ...

Context architecture is replacing RAG as agentic AI pushes enterprise retrieval to its limits

Redis Iris launches as enterprises shift from RAG to runtime context — hybrid retrieval intent tripled in Q1 2026 as agent ...
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 ...
InfoWorld

Your AI doesn’t need another database

For most enterprise applications, vector support is a feature that should be woven into the existing data estate, not a ...
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 ...
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 ...
InfoWorld

Using the Pinecone vector database in .NET

If you’re building generative AI applications, you need to control the data used to generate answers to user queries. Simply dropping ChatGPT into your platform isn’t going to work, especially if ...
TechCrunch

Voyage AI is building RAG tools to make AI hallucinate less

AI tends to make things up. That’s unappealing to just about anyone who uses it on a regular basis, but especially to businesses, for which fallacious results could hurt the bottom line. Half of ...
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

Bringing Your Own Data to Generative AI with RAG

However, when it comes to adding generative AI capabilities to enterprise applications, we usually find that something is missing—the generative AI programs simply don't have the context to interact ...