diff --git a/docs/source/guide/bedrock.rst b/docs/source/guide/bedrock.rst
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+.. Copyright 2010-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+
+   This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0
+   International License (the "License"). You may not use this file except in compliance with the
+   License. A copy of the License is located at http://creativecommons.org/licenses/by-nc-sa/4.0/.
+
+   This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
+   either express or implied. See the License for the specific language governing permissions and
+   limitations under the License.
+
+.. _guide_bedrock:
+
+#########################
+Amazon Bedrock Runtime
+#########################
+
+.. contents:: **Topics**
+    :depth: 2
+    :local:
+
+Overview
+--------
+
+`Amazon Bedrock <https://aws.amazon.com/bedrock/>`_ is a fully managed service that provides
+access to foundation models (FMs) from leading AI companies through a unified API. This guide
+covers common use cases for the ``bedrock-runtime`` client using the
+`Converse API <https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html>`_,
+which is the recommended approach for conversational use cases.
+
+Prerequisites
+~~~~~~~~~~~~~
+
+Before getting started, ensure you have:
+
+* An AWS account with Amazon Bedrock access enabled
+* Model access granted for your desired foundation model in the
+  `Bedrock console <https://console.aws.amazon.com/bedrock/home#/modelaccess>`_
+* Boto3 installed and configured with appropriate IAM permissions
+
+The examples below use ``us.anthropic.claude-opus-4-6-v1:0``. You can substitute any
+`supported model ID <https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html>`_.
+
+.. _bedrock_converse:
+
+Send a message with the Converse API
+--------------------------------------
+
+The Converse API provides a unified interface across all supported models and handles the
+message format automatically. It is the recommended API for text-based conversational use cases.
+
+.. code-block:: python
+
+    import boto3
+
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    response = client.converse(
+        modelId="us.anthropic.claude-opus-4-6-v1:0",
+        messages=[
+            {
+                "role": "user",
+                "content": [{"text": "What is Amazon Bedrock?"}],
+            }
+        ],
+        inferenceConfig={
+            "maxTokens": 512,
+            "temperature": 0.7,
+        },
+    )
+
+    print(response["output"]["message"]["content"][0]["text"])
+
+.. _bedrock_system_prompt:
+
+Use a system prompt
+---------------------
+
+You can include a system prompt to set the model's behavior and context.
+
+.. code-block:: python
+
+    import boto3
+
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    response = client.converse(
+        modelId="us.anthropic.claude-opus-4-6-v1:0",
+        system=[
+            {"text": "You are a helpful assistant that responds concisely."}
+        ],
+        messages=[
+            {
+                "role": "user",
+                "content": [{"text": "Explain what an S3 bucket is."}],
+            }
+        ],
+    )
+
+    print(response["output"]["message"]["content"][0]["text"])
+
+.. _bedrock_multi_turn:
+
+Multi-turn conversation
+-----------------------
+
+The Converse API supports multi-turn conversations by passing the conversation history in the
+``messages`` parameter.
+
+.. code-block:: python
+
+    import boto3
+
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    messages = [
+        {"role": "user", "content": [{"text": "What is AWS Lambda?"}]},
+        {
+            "role": "assistant",
+            "content": [
+                {
+                    "text": "AWS Lambda is a serverless compute service that runs your code "
+                    "in response to events without requiring you to manage servers."
+                }
+            ],
+        },
+        {"role": "user", "content": [{"text": "How does it differ from EC2?"}]},
+    ]
+
+    response = client.converse(
+        modelId="us.anthropic.claude-opus-4-6-v1:0",
+        messages=messages,
+    )
+
+    print(response["output"]["message"]["content"][0]["text"])
+
+.. _bedrock_streaming:
+
+Stream a response
+-----------------
+
+Use ``converse_stream`` to receive the model's response incrementally as it is generated.
+This is useful for displaying responses in real time.
+
+.. code-block:: python
+
+    import boto3
+
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    response = client.converse_stream(
+        modelId="us.anthropic.claude-opus-4-6-v1:0",
+        messages=[
+            {
+                "role": "user",
+                "content": [{"text": "Write a short poem about cloud computing."}],
+            }
+        ],
+    )
+
+    stream = response.get("stream")
+    if stream:
+        for event in stream:
+            if "contentBlockDelta" in event:
+                delta = event["contentBlockDelta"]["delta"]
+                if "text" in delta:
+                    print(delta["text"], end="", flush=True)
+    print()  # newline after streaming completes
+
+.. _bedrock_cross_region:
+
+Cross-region inference
+----------------------
+
+Cross-region inference routes requests across multiple AWS Regions for higher throughput and
+availability during peak demand. To enable it, prefix your model ID with the inference profile
+prefix (e.g., ``us.`` for the US geography).
+
+.. code-block:: python
+
+    import boto3
+
+    # Use us-east-1 as the entry point; Bedrock routes to the optimal region automatically
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    response = client.converse(
+        modelId="us.anthropic.claude-opus-4-6-v1:0",  # note the "us." prefix
+        messages=[
+            {
+                "role": "user",
+                "content": [{"text": "Summarize the benefits of cross-region inference."}],
+            }
+        ],
+    )
+
+    print(response["output"]["message"]["content"][0]["text"])
+
+.. note::
+
+    Cross-region inference profiles are available for select models. See
+    `Supported Regions and models <https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-support.html>`_
+    for the full list.
+
+.. _bedrock_error_handling:
+
+Error handling
+--------------
+
+Handle common Bedrock errors such as throttling and model-specific exceptions.
+
+.. code-block:: python
+
+    import boto3
+    from botocore.exceptions import ClientError
+
+    client = boto3.client("bedrock-runtime", region_name="us-east-1")
+
+    try:
+        response = client.converse(
+            modelId="us.anthropic.claude-opus-4-6-v1:0",
+            messages=[
+                {"role": "user", "content": [{"text": "Hello!"}]}
+            ],
+        )
+        print(response["output"]["message"]["content"][0]["text"])
+
+    except client.exceptions.ThrottlingException:
+        print("Request was throttled. Consider adding retry logic with exponential backoff.")
+    except client.exceptions.ModelNotReadyException:
+        print("The model is not ready. Ensure model access is enabled in the Bedrock console.")
+    except ClientError as e:
+        print(f"Unexpected error: {e.response['Error']['Message']}")
diff --git a/docs/source/guide/examples.rst b/docs/source/guide/examples.rst
index a38fbfca88..f24af6960d 100644
--- a/docs/source/guide/examples.rst
+++ b/docs/source/guide/examples.rst
@@ -40,3 +40,4 @@ described in :doc:`quickstart`.
    secrets-manager
    ses-examples
    sqs-examples
+   bedrock