diff --git a/docs.json b/docs.json
index 9321fdd7..2d0d29fa 100644
--- a/docs.json
+++ b/docs.json
@@ -252,7 +252,8 @@
                   "integrations/llms/bedrock/files",
                   "integrations/llms/bedrock/batches",
                   "integrations/llms/bedrock/fine-tuning",
-                  "integrations/llms/bedrock/prompt-caching"
+                  "integrations/llms/bedrock/prompt-caching",
+                  "integrations/llms/bedrock/embeddings"
                 ]
               },
               "integrations/llms/aws-sagemaker",
diff --git a/integrations/llms/bedrock/embeddings.mdx b/integrations/llms/bedrock/embeddings.mdx
new file mode 100644
index 00000000..e00f7cfe
--- /dev/null
+++ b/integrations/llms/bedrock/embeddings.mdx
@@ -0,0 +1,455 @@
+---
+title: "Embeddings"
+description: "Get embeddings from Bedrock"
+---
+
+Bedrock supports embedding text and images through Amazon Titan and Cohere models.
+Portkey provides a standardized interface for embedding multiple modalities.
+
+# Bedrock Titan
+
+## Embedding Text
+<CodeGroup>
+    ```python Python
+    from portkey_ai import Portkey
+
+    client = Portkey(
+        api_key="YOUR_PORTKEY_API_KEY", # defaults to os.environ.get("PORTKEY_API_KEY")
+        virtual_key="VIRTUAL_KEY",
+    )
+
+    embeddings = client.embeddings.create(
+        model="amazon.titan-embed-text-v2:0",
+        input="Hello this is a test",
+        # normalize=False # if you would like to disable normalization
+        # dimensions=1024, # embedding dimensions
+        # encoding_format="float", # embedding format
+    )
+    ```
+
+    ```javascript NodeJS
+    import { Portkey } from 'portkey-ai';
+
+    const portkey = new Portkey({
+        apiKey: "YOUR_API_KEY",
+        virtualKey: "YOUR_VIRTUAL_KEY"
+    });
+
+    const embedding = await portkey.embeddings.create({
+        model: "amazon.titan-embed-text-v2:0",
+        input: "Hello this is a test",
+        // normalize: false, // if you would like to disable normalization
+        // dimensions: 1024, // embedding dimensions
+        // encoding_format: "float", // embedding format
+    });
+
+    console.log(embedding);
+    ```
+
+    ```sh cURL
+    curl --location 'https://api.portkey.ai/v1/embeddings' \
+    --header 'Content-Type: application/json' \
+    --header 'x-portkey-api-key: PORTKEY_API_KEY' \
+    --header 'x-portkey-virtual-key: PORTKEY_VIRTUAL_KEY' \
+    --data-raw '{
+        "model": "amazon.titan-embed-text-v2:0",
+        "input": "Hello this is a test",
+        "normalize": false, // if you would like to disable normalization
+        "dimensions": 1024, // embedding dimensions
+        "encoding_format": "float" // embedding format
+    }'
+    ```
+
+    ```python OpenAI Python
+    from openai import OpenAI
+    from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+    portkey_client = OpenAI(
+        api_key='NOT_REQUIRED',
+        base_url=PORTKEY_GATEWAY_URL,
+        default_headers=createHeaders(
+            provider="openai",
+            api_key="PORTKEY_API_KEY"
+        )
+    )
+
+    embeddings = portkey_client.embeddings.create(
+        model="amazon.titan-embed-text-v2:0",
+        input="Hello this is a test",
+        # normalize=False # if you would like to disable normalization
+        # dimensions=1024, # embedding dimensions
+        # encoding_format="float", # embedding format
+    )
+    ```
+
+    ```js OpenAI NodeJS
+    import OpenAI from 'openai'; // We're using the v4 SDK
+    import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'
+
+    const portkeyClient = new OpenAI({
+      apiKey: 'NOT_REQUIRED', // defaults to process.env["OPENAI_API_KEY"],
+      baseURL: PORTKEY_GATEWAY_URL,
+      defaultHeaders: createHeaders({
+        provider: "vertex-ai",
+        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
+        virtualKey: "PORTKEY_VIRTUAL_KEY"
+      })
+    });
+
+    const embedding = await portkeyClient.embeddings.create({
+        model: "amazon.titan-embed-text-v2:0",
+        input: "Hello this is a test",
+        // normalize=False, // if you would like to disable normalization
+        // dimensions=1024, // embedding dimensions
+        // encoding_format="float", // embedding format
+    });
+
+    console.log(embedding);
+    ```
+
+</CodeGroup>
+
+## Embeddings Images
+
+<CodeGroup>
+    ```python Python
+    from portkey_ai import Portkey
+
+    client = Portkey(
+        api_key="YOUR_PORTKEY_API_KEY", # defaults to os.environ.get("PORTKEY_API_KEY")
+        virtual_key="VIRTUAL_KEY",
+    )
+
+    embeddings = client.embeddings.create(
+        model="amazon.titan-embed-image-v1",
+        dimensions=256,
+        input=[
+        {
+            "text": "this is the caption of the image",
+            "image": {
+                "base64": "UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    )
+    ```
+
+    ```javascript NodeJS
+    import { Portkey } from 'portkey-ai';
+
+    const portkey = new Portkey({
+        apiKey: "YOUR_API_KEY",
+        virtualKey: "YOUR_VIRTUAL_KEY"
+    });
+
+    const embedding = await portkey.embeddings.create({
+        model: "amazon.titan-embed-image-v1",
+        dimensions: 256,
+        input: [
+        {
+            "text": "this is the caption of the image",
+            "image": {
+                "base64": "UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    });
+
+    console.log(embedding);
+    ```
+
+    ```sh cURL
+    curl --location 'https://api.portkey.ai/v1/embeddings' \
+    --header 'Content-Type: application/json' \
+    --header 'x-portkey-api-key: PORTKEY_API_KEY' \
+    --header 'x-portkey-virtual-key: PORTKEY_VIRTUAL_KEY' \
+    --data-raw '{
+    "model": "amazon.titan-embed-image-v1",
+    "dimensions": 256,
+    "input": [
+        {
+            "text": "this is the caption of the image",
+            "image": {
+                "base64": "UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    }'
+    ```
+
+    ```python OpenAI Python
+    from openai import OpenAI
+    from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+    portkey_client = OpenAI(
+        api_key='NOT_REQUIRED',
+        base_url=PORTKEY_GATEWAY_URL,
+        default_headers=createHeaders(
+            provider="openai",
+            api_key="PORTKEY_API_KEY"
+        )
+    )
+
+    embeddings = portkey_client.embeddings.create(
+        model="amazon.titan-embed-image-v1",
+        dimensions=256,
+        input=[
+        {
+            "text": "this is the caption of the image",
+            "image": {
+                "base64": "UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+        ]
+    )
+    ```
+
+    ```js OpenAI NodeJS
+    import OpenAI from 'openai'; // We're using the v4 SDK
+    import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'
+
+    const portkeyClient = new OpenAI({
+      apiKey: 'NOT_REQUIRED', // defaults to process.env["OPENAI_API_KEY"],
+      baseURL: PORTKEY_GATEWAY_URL,
+      defaultHeaders: createHeaders({
+        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
+        virtualKey: "PORTKEY_VIRTUAL_KEY"
+      })
+    });
+
+    const embedding = await portkeyClient.embeddings.create({
+        model: "amazon.titan-embed-image-v1",
+        dimensions: 256,
+        input: [
+        {
+            text: "this is the caption of the image",
+            image: {
+                base64: "UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+        ]
+    });
+
+    console.log(embedding);
+    ```
+
+</CodeGroup>
+
+# Cohere
+
+## Embedding Text
+<CodeGroup>
+    ```python Python
+    from portkey_ai import Portkey
+
+    client = Portkey(
+        api_key="YOUR_PORTKEY_API_KEY", # defaults to os.environ.get("PORTKEY_API_KEY")
+        virtual_key="VIRTUAL_KEY",
+    )
+
+    embeddings = client.embeddings.create(
+        model="cohere.embed-english-v3",
+        input=["Hello this is a test", "skibidi"],
+        input_type="classification"
+    )
+    ```
+
+    ```javascript NodeJS
+    import { Portkey } from 'portkey-ai';
+
+    const portkey = new Portkey({
+        apiKey: "YOUR_API_KEY",
+        virtualKey: "YOUR_VIRTUAL_KEY"
+    });
+
+    const embedding = await portkey.embeddings.create({
+        model: "cohere.embed-english-v3",
+        input: ["Hello this is a test", "skibidi"],
+        input_type: "classification"
+    });
+
+    console.log(embedding);
+    ```
+
+    ```sh cURL
+    curl --location 'https://api.portkey.ai/v1/embeddings' \
+    --header 'Content-Type: application/json' \
+    --header 'x-portkey-api-key: PORTKEY_API_KEY' \
+    --header 'x-portkey-virtual-key: PORTKEY_VIRTUAL_KEY' \
+    --data-raw '{
+      "model": "cohere.embed-english-v3",
+      "input": ["Hello this is a test", "skibidi"],
+      "input_type": "classification"
+    }'
+    ```
+
+    ```python OpenAI Python
+    from openai import OpenAI
+    from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+    portkey_client = OpenAI(
+        api_key='NOT_REQUIRED',
+        base_url=PORTKEY_GATEWAY_URL,
+        default_headers=createHeaders(
+            provider="openai",
+            api_key="PORTKEY_API_KEY"
+        )
+    )
+
+    embeddings = portkey_client.embeddings.create(
+        model="cohere.embed-english-v3",
+        input=["Hello this is a test", "skibidi"],
+        input_type="classification"
+    )
+    ```
+
+    ```js OpenAI NodeJS
+    import OpenAI from 'openai'; // We're using the v4 SDK
+    import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'
+
+    const portkeyClient = new OpenAI({
+      apiKey: 'NOT_REQUIRED', // defaults to process.env["OPENAI_API_KEY"],
+      baseURL: PORTKEY_GATEWAY_URL,
+      defaultHeaders: createHeaders({
+        provider: "vertex-ai",
+        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
+        virtualKey: "PORTKEY_VIRTUAL_KEY"
+      })
+    });
+
+    const embedding = await portkeyClient.embeddings.create({
+        model: "cohere.embed-english-v3",
+        input: ["Hello this is a test", "skibidi"],
+        input_type: "classification"
+    });
+
+    console.log(embedding);
+    ```
+
+</CodeGroup>
+
+## Embeddings Images
+
+<CodeGroup>
+    ```python Python
+    from portkey_ai import Portkey
+
+    client = Portkey(
+        api_key="YOUR_PORTKEY_API_KEY", # defaults to os.environ.get("PORTKEY_API_KEY")
+        virtual_key="VIRTUAL_KEY",
+    )
+
+    embeddings = client.embeddings.create(
+        model="cohere.embed-english-v3",
+        input_type="image",
+        dimensions=256,
+        input=[
+        {
+            "image": {
+                "base64": "Data:image/webp;base64,UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    )
+    ```
+
+    ```javascript NodeJS
+    import { Portkey } from 'portkey-ai';
+
+    const portkey = new Portkey({
+        apiKey: "YOUR_API_KEY",
+        virtualKey: "YOUR_VIRTUAL_KEY"
+    });
+
+    const embedding = await portkey.embeddings.create({
+    "model": "cohere.embed-english-v3",
+    "input_type": "image",
+    "dimensions": 256,
+    "input": [
+        {
+            "image": {
+                "base64": "Data:image/webp;base64,UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    });
+
+    console.log(embedding);
+    ```
+
+    ```sh cURL
+    curl --location 'https://api.portkey.ai/v1/embeddings' \
+    --header 'Content-Type: application/json' \
+    --header 'x-portkey-api-key: PORTKEY_API_KEY' \
+    --header 'x-portkey-virtual-key: PORTKEY_VIRTUAL_KEY' \
+    --data-raw '{
+    "model": "cohere.embed-english-v3",
+    "input_type": "image",
+    "dimensions": 256,
+    "input": [
+        {
+            "image": {
+                "base64": "Data:image/webp;base64,UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    }'
+    ```
+
+    ```python OpenAI Python
+    from openai import OpenAI
+    from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+    portkey_client = OpenAI(
+        api_key='NOT_REQUIRED',
+        base_url=PORTKEY_GATEWAY_URL,
+        default_headers=createHeaders(
+            provider="openai",
+            api_key="PORTKEY_API_KEY"
+        )
+    )
+
+    embeddings = portkey_client.embeddings.create(
+        model="cohere.embed-english-v3",
+        input_type="image",
+        dimensions=256,
+        input=[
+        {
+            image: {
+                base64: "Data:image/webp;base64,UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+    ]
+    )
+    ```
+
+    ```js OpenAI NodeJS
+    import OpenAI from 'openai'; // We're using the v4 SDK
+    import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'
+
+    const portkeyClient = new OpenAI({
+      apiKey: 'NOT_REQUIRED', // defaults to process.env["OPENAI_API_KEY"],
+      baseURL: PORTKEY_GATEWAY_URL,
+      defaultHeaders: createHeaders({
+        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
+        virtualKey: "PORTKEY_VIRTUAL_KEY"
+      })
+    });
+
+    const embedding = await portkeyClient.embeddings.create({
+        model: "cohere.embed-english-v3",
+        input_type: "image",
+        dimensions: 256,
+        input: [
+        {
+            image: {
+                base64: "Data:image/webp;base64,UklGRkacAABXRUJQVlA4IDqcAACQggKdASqpAn8B....."
+            }
+        }
+      ]
+    });
+
+    console.log(embedding);
+    ```
+
+</CodeGroup>
\ No newline at end of file