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Grounding

Grounding is supplying a model with the sources it should rely on before it answers, so the output is constrained by evidence rather than by the model's guesswork. It improves what goes into generation; it does not test what came out, which is verification's job. The two are parallel disciplines, not interchangeable ones: a well-grounded system can still produce a fluent claim no source supports.

Related terms

AI VerificationHallucinationCOVEContext Engineering

Where this term is used

On Nucleus

  • Playbook

    Add Nucleus to ChatGPT

    ChatGPT supports custom MCP connectors. Nucleus is an MCP endpoint. So Nucleus adds in as a custom connector and becomes ChatGPT's one grounded, joined memory across every source.

  • Playbook

    Nucleus + ClickUp task flow

    Wire your ClickUp tasks and docs into one reasoning layer.

On The AI Brain

  • Research

    The Al Jazeera Research Demonstration

    Same frontier model, three conditions, categorically different output.

  • Research

    When Context Collapses: What a Geopolitical Crisis Revealed About AI's *Missing Layer*

    During the Iran-US escalation cycle, we ran frontier AI models against the same questions under different context architectures. Five failure modes emerged that no model upgrade will fix. They are pr…

  • Use case

    Client-Ready Intelligence, Co-Built and White-Labeled

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