Vector databases as a service

What we offer

We handle setup, operations and optimization of vector databases for customers. We support architecture decisions as well as ongoing operations, monitoring and tuning. Our experience is based on Administrator.de with millions of records that keep growing, as well as on our SaaS AI assistant.

High-performance search with vector databases

Vector databases are the best foundation for high‑performance search. We work with RFF indexes (dense and sparse), which significantly improves quality and relevance. The result is fast, precise answers for search, RAG and semantic applications. Converting data into vectors takes time and compute resources — but it yields much faster results during retrieval. Especially at large scale, this upfront work pays off with millisecond response times and better relevance.

What are vector databases?

Vector databases store information as numerical vectors, allowing searches by meaning rather than exact keywords. A text, image or document is transformed into a vector that represents its semantics. Search compares vectors and returns the most similar results. This makes vector databases the foundation for semantic search, chatbots and RAG systems. Performance depends on index structure, embedding quality and query strategy.