> ## Documentation Index
> Fetch the complete documentation index at: https://docs.guardion.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Grounding

> Detect hallucinations and ungrounded claims in RAG and agentic workflows

The Grounding detector identifies hallucinations and ungrounded claims in AI-generated responses. It verifies that assistant outputs are faithfully supported by the provided context, retrieved documents, or tool call results — critical for RAG pipelines and agentic workflows.

## What it detects

* Responses that contradict or are unsupported by retrieved context (groundedness)

## Available models (versions)

* [Guardion-1-8B](/guardion-1-8b) — multilingual grounding and hallucination detection

See the detailed model card in [Guardion-1-8B](/guardion-1-8b) for architecture and benchmarks.

## Detection Categories

| Category               | Status      | Description                                                                                                                                 |
| :--------------------- | :---------- | :------------------------------------------------------------------------------------------------------------------------------------------ |
| **GROUNDEDNESS**       | Available   | Assistant's response includes claims or facts not supported by or contradicted by the provided context.                                     |
| **CONTEXT\_RELEVANCE** | Coming soon | Retrieved context is not pertinent to answering the user's question or addressing their needs.                                              |
| **ANSWER\_RELEVANCE**  | Coming soon | Assistant's response fails to address or properly respond to the user's input.                                                              |
| **FUNCTION\_CALL**     | Coming soon | Assistant's response contains function calls that have syntax or semantic errors based on the user query and available tools.               |
| **AGENT\_CHAIN**       | Coming soon | Agent traces contain dangerous action chains or combinations, looping behaviors, or irrelevant actions that deviate from the intended task. |

## Dashboard Output

In the Guardion dashboard, the Grounding guardrail displays a binary **SAFE / UNSAFE** verdict for each evaluated response, along with the confidence score. This makes it easy to monitor grounding quality at a glance and drill into individual flagged responses for investigation.

## Using the Grounding detector

```js theme={null}
// 1) Create or update a Grounding policy
await fetch("https://api.guardion.ai/v1/policies", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_API_KEY"
  },
  body: JSON.stringify({
    id: "grounding-check",
    definition: "Detect hallucinations and ungrounded claims",
    threshold: 0.9, // L1 (Confident). Use 0.8 for L2, 0.7 for L3, 0.6 for L4
    detector: {
      model: "grounding",
      target: "assistant",
    }
  })
});

// 2) Evaluate using that policy
const response = await fetch("https://api.guardion.ai/v1/guard", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_API_KEY"
  },
  body: JSON.stringify({
    messages: [
      { role: "context", content: "Our return policy allows returns within 14 days of purchase." }, // or "system" role
      { role: "user", content: "What is the return policy?" },
      { role: "assistant", content: "The return policy allows returns within 30 days." }
    ],
    policy: "grounding-check"
  })
});
```

### Threshold levels

* L1 (0.9): Confident
* L2 (0.8): Very Likely
* L3 (0.7): Likely
* L4 (0.6): Less Likely

## Notes

* Best suited for RAG pipelines where factual accuracy against retrieved documents is critical.
* Combine with Injection and Moderation detectors for comprehensive runtime safety.

## Related

* Guardion-1-8B Model Card: [/guardion-1-8b](/guardion-1-8b)