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

# Data Privacy in Model Inference

> How Model Inference keeps your data secure within your infrastructure

Model Inference is designed with data privacy as a foundational principle. Unlike traditional AI services that require sending data to external providers, Model Inference runs entirely within your [data plane](/concepts/primitives/data-planes), ensuring your data never leaves your controlled infrastructure.

## The privacy challenge with external AI

When using external AI APIs (OpenAI API, Anthropic API, etc.), your data flows to third-party servers:

```mermaid theme={null}
sequenceDiagram
    participant App as Your Application
    participant API as External AI API
    participant Provider as AI Provider Servers

    App->>API: Send data for inference
    API->>Provider: Data processed externally
    Note over Provider: Data potentially logged,<br/>retained, or used for training
    Provider->>API: Return response
    API->>App: Response
```

This creates several concerns:

* **Data residency**: Data leaves your infrastructure and jurisdiction
* **Third-party access**: Provider can potentially access your data
* **Compliance complexity**: Must evaluate provider's data handling practices
* **Retention policies**: Provider may retain data for improvement or debugging

## How Model Inference protects your data

Model Inference eliminates these concerns by hosting models within your data plane:

```mermaid theme={null}
sequenceDiagram
    participant App as Your Application
    participant CP as Control Plane
    participant DP as Your Data Plane
    participant Model as Hosted LLM

    App->>CP: Submit inference request
    Note over CP: Only job metadata<br/>(no raw data)
    CP->>DP: Route job to data plane
    DP->>Model: Local inference
    Note over Model: Model runs in<br/>your infrastructure
    Model->>DP: Response
    DP->>CP: Job completion status
    CP->>App: Structured output
```

### Key privacy guarantees

| Aspect                  | Guarantee                                                    |
| ----------------------- | ------------------------------------------------------------ |
| **Data location**       | Data never leaves your data plane                            |
| **No external calls**   | No network requests to Anthropic, OpenAI, or other providers |
| **Your infrastructure** | Models run on compute within your environment                |
| **No provider logging** | AI providers have no access to your data                     |
| **Full control**        | You control data access, retention, and deletion             |

## Compliance implications

Model Inference simplifies compliance with data protection regulations:

### GDPR considerations

* **Data minimization**: Only necessary data is processed
* **Storage limitation**: You control retention within your data plane
* **Data transfers**: No cross-border transfers to AI providers
* **Processor agreements**: No need for DPAs with AI providers for inference

### CCPA considerations

* **Service provider status**: AI providers are not service providers for your data
* **Sale of data**: No data is shared with third parties
* **Right to delete**: Full control over data deletion

### Industry regulations

For industries with strict data handling requirements (healthcare, finance, government), Model Inference enables AI capabilities without the compliance burden of external AI services:

* **HIPAA**: PHI never leaves your controlled environment
* **PCI DSS**: Payment data stays within your secure perimeter
* **FedRAMP**: Data remains in authorized boundaries

## Audit trail

All inference jobs are tracked through Narrative's standard job system:

* Job creation timestamp
* Data plane where inference ran
* Model used
* Token usage metrics
* Job completion status

This provides a complete audit trail without exposing the actual data processed.

## What the control plane sees

The [control plane](/concepts/primitives/control-plane) only handles:

* Job routing and coordination
* Metadata about requests (model choice, configuration)
* Job status updates
* Token usage statistics

The control plane never receives or processes:

* Your prompt content
* Your data
* The model's responses

## Comparison with external AI

| Aspect               | External AI APIs              | Model Inference           |
| -------------------- | ----------------------------- | ------------------------- |
| Data location        | Provider's servers            | Your data plane           |
| Network traffic      | Data sent externally          | Local only                |
| Provider data access | Yes (per their policies)      | No                        |
| Compliance burden    | High (must evaluate provider) | Low (your infrastructure) |
| Audit complexity     | Must rely on provider logs    | Full control              |
| Data retention       | Provider-controlled           | You control               |

## Best practices

1. **Use appropriate models**: Don't send more context than necessary
2. **Review prompts**: Ensure prompts don't unnecessarily include sensitive data
3. **Monitor usage**: Track inference jobs through the job system
4. **Set retention policies**: Configure data plane retention appropriately

## Related content

<CardGroup cols={2}>
  <Card title="Model Inference Overview" icon="brain" href="/concepts/model-inference/overview">
    How Model Inference works
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    Understanding data plane architecture
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    Platform security architecture
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