What is a vector database?

A vector database is a specialized system designed to store, manage, and index high-dimensional numerical representations of information called vectors or embeddings. It is the type of database used for retrieval-augmented generation (RAG), which adds relevant context to AI model interactions.

How does a vector database work?

AI models convert content such as documents, images, or other data into vectors that represent meaning. The database can then find information based on similarity and context instead of relying only on exact keyword matches.

Why is a vector database important?

Vector databases are growing in popularity because they provide the speed and performance organizations need for generative AI (GenAI) applications and use cases. They quickly find relevant information and can help integrate an organization’s own data into AI output.

Benefits and use cases

• Higher-quality answers in RAG applications
• Semantic search across documents, tickets, and knowledge bases
• Personalization and recommendation scenarios
• Fast retrieval for large-scale unstructured data

Does NexusTek help with vector database use?

Yes. NexusTek helps organizations operationalize AI and data faster by aligning infrastructure and platforms to business outcomes, from cloud foundations through managed services that support AI applications like RAG.