Retrieval, Memory & Knowledge

Grounding

Connecting AI outputs to verified real-world information to reduce hallucination.

Definition

Grounding refers to anchoring an AI model's responses in specific, verifiable sources rather than relying solely on the model's parametric knowledge. A grounded AI response will cite the specific document or data source it drew on, making it possible to verify the claim independently. Grounding through RAG is one of the most effective techniques for reducing hallucination in business-critical AI deployments.

Heard enough terminology — ready to talk outcomes?

We translate AI concepts into measurable business results. No upfront fees — you pay only when independently verified results are delivered.

← Back to glossary

Disclaimer

This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.

Document reference: ISO_webpage_knowledge-base_glossary_v1

Last modified: 29 March 2026

Knowledge Base·Retrieval, Memory & Knowledge·Grounding