White Paper
How to Build AI-driven Knowledge Assistants with a Vector Store, LLMs, and RAG Pipelines
CrateDB is the enterprise database for time series, documents and vectors. It combines the simplicity of SQL, and the performance of NoSQL, providing instant insights into these different types of data. It is enabled for AI and is used for a large variety of use cases, including Real-time Analytics, AI/ML, chatbots, IoT, digital twins, log analysis, cyber security, application monitoring, and database consolidation.
This white paper explores how CrateDB provides a scalable platform to build Generative AI applications that cover the requirements of modern applications, such as AI-driven knowledge assistants. CrateDB is not just handling vectors, but also provides in a single storage engine a unique combination of all the data types needed for end-to-end applications, including RAG pipelines.
What you will learn
- What the key concepts of Generative AI are and what common challenges are
- How to provide custom context and private data in Generative AI
- What the architecture of knowledge assistants looks like
- How to implement a vector store with CrateDB
- How TGW Logistics Group is using CrateDB to develop their Digital Knowledge Assistants