Grounding
Grounding is the process of providing an AI model with relevant and trusted information so it can generate accurate, context-aware, and fact-based responses.
What is Grounding?
Grounding connects an AI model's responses to reliable external information, such as databases, documents, knowledge bases, or retrieved sources. Instead of relying only on information learned during training, the model can use this contextual information when generating a response.
Why is Grounding Important?
Grounding helps improve the accuracy and relevance of AI-generated responses and can reduce hallucinations. It is particularly important for applications that require current, domain-specific, or organization-specific information.
Common use cases
Grounding is commonly used in RAG systems, enterprise AI assistants, chatbots, document analysis, customer support, search applications, and AI systems that need access to current or private information.