data-residency

manage-claude/data-residency First recorded · 324 lines, first recorded

## Inference geo ### API usage ### Response ### Model availability ### Workspace-level restrictions ## Workspace geo ## Pricing ## Batch API support ## Migration from legacy opt-outs ### What changed ### What happened to your workspace ### If you want to use global routing ### Pricing impact ## Current limitations ## Next steps

The first capture of this source. The page was already there, and this is what it said.

---
title: Data residency
url: https://platform.claude.com/docs/en/manage-claude/data-residency
description: Manage where model inference runs and where data is stored with geographic controls.
---

Data residency controls let you manage where your data is processed and stored. Two independent settings govern this:

* **Inference geo:** Controls where model inference runs, on a per-request basis. Set through the `inference_geo` API parameter or as a workspace default.
* **Workspace geo:** Controls where data is stored at rest and where endpoint processing (such as image transcoding and code execution) happens. Configured at the workspace level in the [Claude Console](https://platform.claude.com).

<Note>
  [Claude Managed Agents](https://platform.claude.com/docs/en/managed-agents/overview) supports geographic pinning at the agent level: `inference_geo` on an [agent's model configuration](https://platform.claude.com/docs/en/managed-agents/agent-setup#pin-the-inference-geo) pins the geography that serves model requests for sessions running that agent, with [per-session overrides](https://platform.claude.com/docs/en/managed-agents/sessions#pin-the-inference-geo-for-a-session) at session create. Agents without a pin follow the workspace's default inference geo on each request. Managed Agents also respects the Workspace geo configured in Console, and with [self-hosted sandboxes](https://platform.claude.com/docs/en/managed-agents/self-hosted-sandboxes), tool execution and the sandbox filesystem stay on infrastructure you control.
</Note>

## Inference geo

<Note>
  For how zero data retention (ZDR) applies to this feature, see [API and data retention](https://platform.claude.com/docs/en/manage-claude/api-and-data-retention).
</Note>

The `inference_geo` parameter controls where model inference runs for a specific API request. Add it to any `POST /v1/messages` call.

| Value      | Description                                                                                     |
| ---------- | ----------------------------------------------------------------------------------------------- |
| `"global"` | Default. Inference may run in any available geography for optimal performance and availability. |
| `"us"`     | Inference runs only in US-based infrastructure.                                                 |

### API usage

<CodeGroup>
  ```bash cURL
  curl https://api.anthropic.com/v1/messages \
    -H "x-api-key: $ANTHROPIC_API_KEY" \
    -H "anthropic-version: 2023-06-01" \
    -H "content-type: application/json" \
    -d '{
      "model": "claude-opus-5",
      "max_tokens": 1024,
      "inference_geo": "us",
      "messages": [{
        "role": "user",
        "content": "Summarize the key points of this document."
      }]
    }'
  ```

  ```bash CLI
  ant messages create \
    --model claude-opus-5 \
    --max-tokens 1024 \
    --inference-geo us \
    --message '{role: user, content: "Summarize the key points of this document."}' \
    --transform '{content.#(type=="text").text,usage.inference_geo}' --format yaml
  ```

  ```python Python
  client = anthropic.Anthropic()

  response = client.messages.create(
      model="claude-opus-5",
      max_tokens=1024,
      inference_geo="us",
      messages=[
          {"role": "user", "content": "Summarize the key points of this document."}
      ],
  )

  for block in response.content:
      if block.type == "text":
          print(block.text)
  # Check where inference actually ran
  print(f"Inference geo: {response.usage.inference_geo}")
  ```

  ```typescript TypeScript
  const client = new Anthropic();

  const response = await client.messages.create({
    model: "claude-opus-5",
    max_tokens: 1024,
    inference_geo: "us",
    messages: [
      {
        role: "user",
        content: "Summarize the key points of this document."
      }
    ]
  });

  const textBlock = response.content.find(
    (block): block is Anthropic.TextBlock => block.type === "text"
  );
  console.log(textBlock?.text);
  // Check where inference actually ran
  console.log(`Inference geo: ${response.usage.inference_geo}`);
  ```

  ```csharp C#
  var client = new AnthropicClient();

  var response = await client.Messages.Create(
      new MessageCreateParams
      {
          Model = Model.ClaudeOpus5,
          MaxTokens = 1024,
          InferenceGeo = "us",
          Messages =
          [
              new() { Role = Role.User, Content = "Summarize the key points of this document." },
          ],
      }
  );

  foreach (var block in response.Content)
  {
      if (block.TryPickText(out var textBlock))
      {
          Console.WriteLine(textBlock.Text);
      }
  }

  // Check where inference actually ran
  Console.WriteLine($"Inference geo: {response.Usage.InferenceGeo}");
  ```

  ```go Go
  client := anthropic.NewClient()

  message, err := client.Messages.New(context.Background(), anthropic.MessageNewParams{
  	Model:        anthropic.ModelClaudeOpus5,
  	MaxTokens:    1024,
  	InferenceGeo: anthropic.String("us"),
  	Messages: []anthropic.MessageParam{
  		anthropic.NewUserMessage(anthropic.NewTextBlock("Summarize the key points of this document.")),
  	},
  })
  if err != nil {
  	log.Fatal(err)
  }

  for _, block := range message.Content {
  	if textBlock, ok := block.AsAny().(anthropic.TextBlock); ok {
  		fmt.Println(textBlock.Text)
  	}
  }
  // Check where inference actually ran
  fmt.Printf("Inference geo: %s\n", message.Usage.InferenceGeo)
  ```

  ```java Java
  AnthropicClient client = AnthropicOkHttpClient.fromEnv();

  Message response = client.messages().create(
          MessageCreateParams.builder()
                  .model(Model.CLAUDE_OPUS_5)
                  .maxTokens(1024L)
                  .inferenceGeo("us")
                  .addUserMessage("Summarize the key points of this document.")
                  .build());

  response.content().stream()
          .flatMap(block -> block.text().stream())
          .forEach(textBlock -> IO.println(textBlock.text()));
  // Check where inference actually ran
  IO.println("Inference geo: " + response.usage().inferenceGeo().get());
  ```

  ```php PHP
  $client = new Client();

  $response = $client->messages->create(
      model: 'claude-opus-5',
      maxTokens: 1024,
      inferenceGeo: 'us',
      messages: [
          ['role' => 'user', 'content' => 'Summarize the key points of this document.'],
      ],
  );

  foreach ($response->content as $block) {
      if ($block->type === 'text') {
          echo $block->text, PHP_EOL;
      }
  }
  // Check where inference actually ran
  echo "Inference geo: {$response->usage->inferenceGeo}\n";
  ```

  ```ruby Ruby
  client = Anthropic::Client.new

  response = client.messages.create(
    model: "claude-opus-5",
    max_tokens: 1024,
    inference_geo: "us",
    messages: [
      {role: "user", content: "Summarize the key points of this document."}
    ]
  )

  response.content.each do |block|
    puts block.text if block.type == :text
  end
  # Check where inference actually ran
  puts "Inference geo: #{response.usage.inference_geo}"
  ```
</CodeGroup>

### Response

The response `usage` object includes an `inference_geo` field indicating where inference ran:

```json Output
{
  "usage": {
    "input_tokens": 25,
    "output_tokens": 150,
    "inference_geo": "us"
  }
}
```

### Model availability

The `inference_geo` parameter is supported on Claude 4.6 and later models. Requests with `inference_geo` on Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, or earlier models return a 400 error.

<Note>
  The `inference_geo` parameter is available on the Claude API (first-party) and [Claude Platform on AWS](https://platform.claude.com/docs/en/build-with-claude/claude-platform-on-aws). On Amazon Bedrock and Google Cloud, the inference region is determined by the endpoint URL or inference profile, so `inference_geo` is not applicable. On [Claude in Microsoft Foundry](https://platform.claude.com/docs/en/build-with-claude/claude-in-microsoft-foundry), `inference_geo` is likewise not applicable: deployments hosted on Azure can instead use the US Data Zone Standard deployment type, which keeps inference within the United States. The `inference_geo` parameter is also not available through the [OpenAI SDK compatibility endpoint](https://platform.claude.com/docs/en/cli-sdks-libraries/libraries/openai-sdk).
</Note>

### Workspace-level restrictions

Workspace settings also support restricting which inference geos are available:

* **`allowed_inference_geos`:** Restricts which geos a workspace can use. If a request specifies an `inference_geo` not in this list, the API returns an error.
* **`default_inference_geo`:** Sets the fallback geo when `inference_geo` is omitted from a request. Individual requests can override this by setting `inference_geo` explicitly.

These settings can be configured through the Console or the [Admin API](https://platform.claude.com/docs/en/manage-claude/admin-api) under the `data_residency` field.

## Workspace geo

Workspace geo is set when you create a workspace and can't be changed afterward. Currently, `"us"` is the only available workspace geo.

To set workspace geo, create a new workspace in the [Console](https://platform.claude.com):

1. Go to **Settings** > **Workspaces**.
2. Create a new workspace.
3. Select the workspace geo.

<Note>
  **Claude Platform on AWS:** Workspace geo is not configurable. Claude Managed Agents sessions on this platform run with an effective Workspace geo of `"us"`, which is currently the only available workspace geo. See [Claude Platform on AWS](https://platform.claude.com/docs/en/build-with-claude/claude-platform-on-aws) for data residency considerations specific to that platform.
</Note>

## Pricing

Data residency pricing varies by model generation:

* **Claude 4.6 and later models:** US-only inference (`inference_geo: "us"`) is priced at 1.1x the standard rate across all token pricing categories (input tokens, output tokens, cache writes, and cache reads).
* **Global routing** (`inference_geo: "global"`): Standard pricing applies.
* **Older models:** Don't support `inference_geo` (see [Model availability](https://platform.claude.com/docs/en/manage-claude/data-residency#model-availability)); standard pricing applies. Requests that include the parameter return a 400 error.

This pricing applies to the Claude API (first-party) and Claude Platform on AWS. On Claude in Microsoft Foundry, the same 1.1x multiplier applies to deployments hosted on Azure that use the US Data Zone Standard deployment type. Partner-operated platforms (Bedrock and Google Cloud) have their own regional pricing. See [Data residency pricing](https://platform.claude.com/docs/en/about-claude/pricing#data-residency-pricing) for details.

The same multiplier applies to [Claude Managed Agents](https://platform.claude.com/docs/en/managed-agents/overview): when an agent's [model configuration](https://platform.claude.com/docs/en/managed-agents/agent-setup) pins `inference_geo` to `"us"`, model requests in sessions running that agent are priced at 1.1x the standard rate.

<Note>
  If you have a [Priority Tier](https://platform.claude.com/docs/en/api/service-tiers) commitment, the 1.1x multiplier for US-only inference also affects how tokens are counted against your Priority Tier capacity. Each token consumed with `inference_geo: "us"` draws down 1.1 tokens from your committed TPM, consistent with how other pricing multipliers (such as prompt caching) affect burndown rates.
</Note>

## Batch API support

The `inference_geo` parameter is supported on the [Batch API](https://platform.claude.com/docs/en/build-with-claude/batch-processing). Each request in a batch can specify its own `inference_geo` value.

## Migration from legacy opt-outs

If your organization previously opted out of global routing to keep inference in the US, your workspace has been automatically configured with `allowed_inference_geos: ["us"]` and `default_inference_geo: "us"`. No code changes are required. Your existing data residency requirements continue to be enforced through the new geo controls.

### What changed

The legacy opt-out was an organization-level setting that restricted all requests to US-based infrastructure. The new data residency controls replace this with two mechanisms:

* **Per-request control:** The `inference_geo` parameter lets you specify `"us"` or `"global"` on each API call, giving you request-level flexibility.
* **Workspace controls:** The `default_inference_geo` and `allowed_inference_geos` settings in the Console let you enforce geo policies across all keys in a workspace.

### What happened to your workspace

Your workspace was migrated automatically:

| Legacy setting                   | New equivalent                                                  |
| -------------------------------- | --------------------------------------------------------------- |
| Global routing opt-out (US only) | `allowed_inference_geos: ["us"]`, `default_inference_geo: "us"` |

All API requests using keys from your workspace continue to run on US-based infrastructure. No action is needed to maintain your current behavior.

### If you want to use global routing

If your data residency requirements have changed and you want to take advantage of global routing for better performance and availability, update your workspace's inference geo settings to include `"global"` in the allowed geos and set `default_inference_geo` to `"global"`. See [Workspace-level restrictions](https://platform.claude.com/docs/en/manage-claude/data-residency#workspace-level-restrictions) for details.

### Pricing impact

Cut at 300 lines.