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SurrealDB 3.0 launches with $23M in new funding and a pitch to replace multi-database RAG stacks with a single engine that handles vectors, graphs, and agent memory transactionally.

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 ...

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 ...

Graphwise, the leading Graph AI provider, today announced the immediate availability of GraphRAG, a low-code AI-workflow engine designed to turn "Python prototypes" into production-grade systems ...

Native integrations reduce setup time and ongoing maintenance by making it easy to ingest, index, and continuously ...

‘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 ...

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 ...

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 ...

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 ...