Ever since large language models (LLMs) exploded onto the scene, executives have felt the urgency to apply them enterprise-wide. Successful use cases such as expedited insurance claims, enhanced ...

Combining Neo4j with Claude, MCP, and network monitoring has given the truck giant real-time visibility into how its systems, ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

A TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set, which stood ...

A knowledge graph, is a graph that depicts the relationship between real-world entities, such as objects, events, situations, and concepts. This information is typically stored in a graph database and ...

Researchers from China and Singapore proposed AURA (Active Utility Reduction via Adulteration) to protect GraphRAG systems ...