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In generative AI, grounding is the ability to connect model output to verifiable sources of information. If you provide models with access to specific data sources, then grounding tethers their output to these data and reduces the chances of inventing content. This is particularly important in situations where accuracy and reliability are significant.
Grounding provides the following benefits:
- Reduces model hallucinations, which are instances where the model generates content that isn't factual.
- Anchors model responses to your data sources.
- Provides auditability by providing grounding support, which are links to sources.
You can ground supported-model output in Gemini Enterprise Agent Platform in the following ways:
For language support, see Supported languages for prompts.
What's next
- To learn more about responsible AI best practices and Gemini Enterprise Agent Platform's safety filters, see Responsible AI.
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Last updated 2026-06-26 UTC.
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