Grounded Generation

Grounded generation forces a model's output to be backed by specific source material — retrieved documents, a knowledge base, or search results — rather than whatever it absorbed during training. The model is instructed to answer only from the provided context and, ideally, to cite which passage each claim came from. It's the answer to hallucination: instead of confidently inventing a fact, a grounded system says "not found in the sources" or points to the exact paragraph. For SaaS builders shipping support bots, research tools, or internal Q&A, grounding is what makes AI answers trustworthy enough to expose to customers. It usually pairs with retrieval-augmented generation, which fetches the relevant context first. Practical note: grounding reduces but doesn't eliminate hallucination — models can still misread or over-extrapolate from a source, so surface citations in the UI and let users click through to verify. Measure faithfulness (does the answer match the cited text?) separately from relevance.