diff --git a/container-images/custom-web-servers.mdx b/container-images/custom-web-servers.mdx
index 6cb686a5..0eab95e0 100644
--- a/container-images/custom-web-servers.mdx
+++ b/container-images/custom-web-servers.mdx
@@ -53,7 +53,7 @@ The configuration requires three key parameters:
   For ASGI applications like FastAPI, include the appropriate server package
   (like `uvicorn`) in your dependencies. After deployment, your endpoints become
   available at
-  `https://api.aws.us-east-1.cerebrium.ai/v4/[project-id]/[app-name]/your/endpoint`.
+  `https://api.cerebrium.ai/v4/p-xxxxxxxx/[app-name]/your/endpoint`.
 </Info>
 
 The [FastAPI Server Example](https://github.com/CerebriumAI/examples) provides a complete implementation.
diff --git a/container-images/defining-container-images.mdx b/container-images/defining-container-images.mdx
index 7a50dc95..1e125f15 100644
--- a/container-images/defining-container-images.mdx
+++ b/container-images/defining-container-images.mdx
@@ -273,7 +273,7 @@ vllm = "latest"
 - Code is mounted in `/cortex` - adjust paths accordingly.
 - The port in your entrypoint must match the `port` parameter.
 - Install any required server packages (uvicorn, gunicorn, etc.) via pip dependencies.
-- All endpoints will be available at `https://api.cerebrium.ai/v4/{project-id}/{app-name}/your/endpoint`.
+- All endpoints will be available at `https://api.cerebrium.ai/v4/p-xxxxxxxx/{app-name}/your/endpoint`.
 
 Deploy with `cerebrium deploy -y` - the system automatically detects custom runtime configuration.
 
diff --git a/deployments/multi-region-deployment.mdx b/deployments/multi-region-deployment.mdx
index ed94b693..4de050d9 100644
--- a/deployments/multi-region-deployment.mdx
+++ b/deployments/multi-region-deployment.mdx
@@ -98,7 +98,7 @@ GPU availability and pricing vary across regions due to infrastructure constrain
 | BLACKWELL_RTX6000 | ❌      | ✅         | ❌      | ❌       | ❌       |
 | AMPERE_A100_80GB  | ✅      | ❌         | ✅      | ✅       | ✅       |
 | AMPERE_A100_40GB  | ✅      | ❌         | ✅      | ✅       | ✅       |
-| ADA_L40S          | ✅      | ❌         | ❌      | ✅       | ❌       |
+| ADA_L40           | ✅      | ❌         | ❌      | ✅       | ❌       |
 | ADA_L4            | ✅      | ❌         | ✅      | ✅       | ✅       |
 | AMPERE_A10        | ✅      | ❌         | ✅      | ✅       | ✅       |
 | TURING_T4         | ✅      | ❌         | ✅      | ✅       | ✅       |
diff --git a/endpoints/async.mdx b/endpoints/async.mdx
index a566a89d..dacd733d 100644
--- a/endpoints/async.mdx
+++ b/endpoints/async.mdx
@@ -8,7 +8,7 @@ Some apps require asynchronous "fire-and-forget" execution. In this model, Cereb
 Enable async execution by adding the `async=true` query parameter to the request:
 
 ```bash
-curl -X POST https://api.aws.us-east-1.cerebrium.ai/v4/<YOUR-PROJECT-ID>/<YOUR-APP>/run?async=true'\
+curl -X POST https://api.cerebrium.ai/v4/p-xxxxxxxx/<YOUR-APP>/run?async=true'\
        -H 'Content-Type: application/json'\
        -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
        --data '{"param": "hello world"}'
@@ -38,7 +38,7 @@ Returning a response while the application is still processing causes Cerebrium
 Because async calls do not return a response to the caller, the function must export any relevant data itself. Combine async execution with a `webhookEndpoint` to have Cerebrium automatically forward the function's response body:
 
 ```bash
-curl -X POST <https://api.aws.us-east-1.cerebrium.ai/v4/><YOUR-PROJECT-ID>/<YOUR-APP>/run?async=true&webhookEndpoint=https%3A%2F%2Fwebhook.site%2F'\
+curl -X POST <https://api.cerebrium.ai/v4/>p-xxxxxxxx/<YOUR-APP>/run?async=true&webhookEndpoint=https%3A%2F%2Fwebhook.site%2F'\
  -H 'Content-Type: application/json'\
  -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
  --data '{"param": "hello world"}'
diff --git a/endpoints/inference-api.mdx b/endpoints/inference-api.mdx
index 370a31c5..328e0a9f 100644
--- a/endpoints/inference-api.mdx
+++ b/endpoints/inference-api.mdx
@@ -10,7 +10,7 @@ All functions on Cerebrium are accessible via authenticated POST requests by def
 The POST request follows the structure below, where `{function}` is the name of the function to invoke. In this example, `predict()` from `main.py` is called.
 
 ```bash
-curl --location --request POST 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxx/{app-name}/{function}' \
+curl --location --request POST 'https://api.cerebrium.ai/v4/p-xxxxxxxx/{app-name}/{function}' \
 --header 'Authorization: Bearer <JWT_TOKEN>' \
 --header 'Content-Type: application/json' \
 --data '{
@@ -18,6 +18,12 @@ curl --location --request POST 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxx
 }'
 ```
 
+<Note>
+  Regioned hostnames such as `https://api.aws.us-east-1.cerebrium.ai` continue
+  to work. Requests to these hostnames are proxied to the global router, which
+  can add latency. Use `https://api.cerebrium.ai` for the lowest-latency path.
+</Note>
+
 ## Response format
 
 Responses follow this format:
diff --git a/endpoints/openai-compatible-endpoints.mdx b/endpoints/openai-compatible-endpoints.mdx
index 88e589b7..d46d82e2 100644
--- a/endpoints/openai-compatible-endpoints.mdx
+++ b/endpoints/openai-compatible-endpoints.mdx
@@ -51,7 +51,7 @@ from openai import OpenAI
 
 client = OpenAI(
     # This is the default and can be omitted
-    base_url="https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxx/1-openai-compatible-endpoint/run", ##This is the name of the function you are calling
+    base_url="https://api.cerebrium.ai/v4/p-xxxxxxxx/1-openai-compatible-endpoint/run", ##This is the name of the function you are calling
     api_key="<CEREBRIUM_JWT_TOKEN>",
 )
 
diff --git a/endpoints/streaming.mdx b/endpoints/streaming.mdx
index af4fd9e7..458de844 100644
--- a/endpoints/streaming.mdx
+++ b/endpoints/streaming.mdx
@@ -22,7 +22,7 @@ def run(upper_range: int):
 Deploy this snippet and call the endpoint. SSE events appear progressively, one per second:
 
 ```bash
-curl -X POST https://api.aws.us-east-1.cerebrium.ai/v4/<YOUR-PROJECT-ID>/2-streaming-endpoint/run \
+curl -X POST https://api.cerebrium.ai/v4/p-xxxxxxxx/2-streaming-endpoint/run \
        -H 'Content-Type: application/json'\
        -H 'Accept: text/event-stream\
        -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
diff --git a/endpoints/webhook.mdx b/endpoints/webhook.mdx
index ed83544a..c0632f15 100644
--- a/endpoints/webhook.mdx
+++ b/endpoints/webhook.mdx
@@ -6,7 +6,7 @@ description: "Forward responses to a specified webhook"
 Forward function response data to an external endpoint via POST by adding the `webhookEndpoint` query parameter to any API call:
 
 ```bash
-curl -X POST https://api.aws.us-east-1.cerebrium.ai/v4/<YOUR-PROJECT-ID>/<YOUR-APP>/run?webhookEndpoint=https%3A%2F%2Fwebhook.site%2F'\
+curl -X POST https://api.cerebrium.ai/v4/p-xxxxxxxx/<YOUR-APP>/run?webhookEndpoint=https%3A%2F%2Fwebhook.site%2F'\
        -H 'Content-Type: application/json'\
        -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
        --data '{"param": "hello world"}'
diff --git a/endpoints/websockets.mdx b/endpoints/websockets.mdx
index 8b898790..0ea371d3 100644
--- a/endpoints/websockets.mdx
+++ b/endpoints/websockets.mdx
@@ -34,7 +34,7 @@ Fields:
 Test the WebSocket endpoint using websocat, a command-line WebSocket client:
 
 ```bash
-websocat wss://api.aws.us-east-1.cerebrium.ai/v4/<your-project-id>/<your-app-name>/<your-websocket-function-name>
+websocat wss://api.cerebrium.ai/v4/p-xxxxxxxx/<your-app-name>/<your-websocket-function-name>
 ```
 
 ## Implementing the WebSocket Endpoint
@@ -61,7 +61,7 @@ Client-side Implementation: Handle the WebSocket connection properly on the clie
 ```javascript
 // Example using JavaScript in a browser
 const socket = new WebSocket(
-  "wss://api.aws.us-east-1.cerebrium.ai/v4/<your-project-id>/<your-app-name>/<your-websocket-function-name>",
+  "wss://api.cerebrium.ai/v4/p-xxxxxxxx/<your-app-name>/<your-websocket-function-name>",
 );
 
 socket.onopen = function (event) {
diff --git a/getting-started/introduction.mdx b/getting-started/introduction.mdx
index a82a7143..1cbf79d8 100644
--- a/getting-started/introduction.mdx
+++ b/getting-started/introduction.mdx
@@ -126,7 +126,7 @@ This turns the function into a persistent [REST endpoint](/endpoints/inference-a
 Once deployed, the app is callable at a POST endpoint:
 
 ```text
-https://api.aws.us-east-1.cerebrium.ai/v4/{project-id}/{app-name}/{function-name}
+https://api.cerebrium.ai/v4/p-xxxxxxxx/{app-name}/{function-name}
 ```
 
 ### 6. What to do next
diff --git a/integrations/vercel.mdx b/integrations/vercel.mdx
index 6df7fbfd..a868f8f2 100644
--- a/integrations/vercel.mdx
+++ b/integrations/vercel.mdx
@@ -42,19 +42,16 @@ See the [Mistral 7B with vLLM example](/v4/examples/mistral-vllm) for deploying
 After deploying the app, the output includes the endpoint URL. Call it from a Vercel project:
 
 ```javascript
-fetch(
-  "https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/mistral-vllm/predict",
-  {
-    method: "POST",
-    headers: {
-      Authorization: `Bearer ${process.env.CEREBRIUM_JWT}`,
-      "Content-Type": "application/json",
-    },
-    body: JSON.stringify({
-      prompt: "What is the capital city of France?",
-    }),
+fetch("https://api.cerebrium.ai/v4/p-xxxxxxxx/mistral-vllm/predict", {
+  method: "POST",
+  headers: {
+    Authorization: `Bearer ${process.env.CEREBRIUM_JWT}`,
+    "Content-Type": "application/json",
   },
-)
+  body: JSON.stringify({
+    prompt: "What is the capital city of France?",
+  }),
+})
   .then((response) => response.json())
   .then((data) => console.log(data))
   .catch((error) => console.error("Error:", error));
diff --git a/migrations/hugging-face.mdx b/migrations/hugging-face.mdx
index 4cc425fc..e28ba5b2 100644
--- a/migrations/hugging-face.mdx
+++ b/migrations/hugging-face.mdx
@@ -186,7 +186,7 @@ Once deployed, you can use your model as follows:
 import requests
 import json
 
-url = "https://api.aws.us-east-1.cerebrium.ai/v4/[PROJECT_NAME]/llama-8b-vllm/run"
+url = "https://api.cerebrium.ai/v4/p-xxxxxxxx/llama-8b-vllm/run"
 
 payload = json.dumps({"prompt": "tell me about yourself"})
 
diff --git a/migrations/mystic.mdx b/migrations/mystic.mdx
index a8cfa74a..66bb56ea 100644
--- a/migrations/mystic.mdx
+++ b/migrations/mystic.mdx
@@ -273,7 +273,7 @@ cerebrium deploy
 Once your app is deployed, you can make requests to your model using the example cURL request below:
 
 ```bash
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/stable-diffusion/predict' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/stable-diffusion/predict' \
 --header 'Content-Type: application/json' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --data '{
diff --git a/partner-services/deepgram.mdx b/partner-services/deepgram.mdx
index d6ffa2a5..d18f0cd3 100644
--- a/partner-services/deepgram.mdx
+++ b/partner-services/deepgram.mdx
@@ -309,7 +309,7 @@ wget https://dpgr.am/bueller.wav
 9. Call the Deepgram endpoint with appropriate parameters:
 
 ```curl
-curl -X POST --data-binary @bueller.wav "https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxx/deepgram/v1/listen?model=nova-3&smart_format=true"
+curl -X POST --data-binary @bueller.wav "https://api.cerebrium.ai/v4/p-xxxxxxxx/deepgram/v1/listen?model=nova-3&smart_format=true"
 ```
 
 Parameters accepted by the Deepgram service can be found in the [speech-to-text API reference](https://developers.deepgram.com/reference/speech-to-text-api/listen-streaming).
diff --git a/partner-services/rime.mdx b/partner-services/rime.mdx
index f688bc1b..4cab74a6 100644
--- a/partner-services/rime.mdx
+++ b/partner-services/rime.mdx
@@ -65,7 +65,7 @@ App Dashboard: https://dashboard.cerebrium.ai/projects/p-xxxxxxxx/apps/p-xxxxxxx
 5. Send requests to the <b>HTTP</b> Rime service using the deployment URL from the output:
 
 ```
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxxxx/rime' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/rime' \
 --header 'Authorization: Bearer <RIME_API_KEY>' \
 --header 'Content-Type: application/json' \
 --header 'Accept: audio/pcm' \
@@ -79,7 +79,7 @@ curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxxxx/rime' \
 For <b>Websockets</b>, send the following
 
 ```
-wss://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxx/rime/ws2?audioFormat=mp3&speaker=cove&modelId=mistv2&phonemizeBetweenBrackets=true
+wss://api.cerebrium.ai/v4/p-xxxxxxxx/rime/ws2?audioFormat=mp3&speaker=cove&modelId=mistv2&phonemizeBetweenBrackets=true
 Authorization Bearer <RIME_API_KEY>
 
 #With a message like:
diff --git a/toml-reference/toml-reference.mdx b/toml-reference/toml-reference.mdx
index a91b172c..ec9c8c23 100644
--- a/toml-reference/toml-reference.mdx
+++ b/toml-reference/toml-reference.mdx
@@ -102,8 +102,8 @@ The `[cerebrium.runtime.custom]` section configures custom web servers and runti
 
 <Info>
   The port specified in entrypoint must match the port parameter. All endpoints
-  will be available at `https://api.aws.us-east-1.cerebrium.ai/v4/{project - id}
-  /{app - name}/your/endpoint`
+  will be available at
+  `https://api.cerebrium.ai/v4/p-xxxxxxxx/your-app-name/your/endpoint`
 </Info>
 
 ## Hardware Configuration
diff --git a/v4/examples/aiVoiceAgents.mdx b/v4/examples/aiVoiceAgents.mdx
index cf6ebe64..32e7bdd5 100644
--- a/v4/examples/aiVoiceAgents.mdx
+++ b/v4/examples/aiVoiceAgents.mdx
@@ -488,7 +488,7 @@ A public fork of the PipeCat frontend demonstrates this application. Clone the r
 Follow the instructions in the README.md and then populate the following variables in your .env.development.local
 
 ```
-VITE_SERVER_URL=https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxx/<APP_NAME> #This is the base url. Do not include the function names
+VITE_SERVER_URL=https://api.cerebrium.ai/v4/p-xxxxxxxx/<APP_NAME> #This is the base url. Do not include the function names
 VITE_SERVER_AUTH= #This is the JWT token you can get from the API Keys section of your Cerebrium Dashboard.
 ```
 
diff --git a/v4/examples/asgi-gradio-interface.mdx b/v4/examples/asgi-gradio-interface.mdx
index 16d7162a..04fca57e 100644
--- a/v4/examples/asgi-gradio-interface.mdx
+++ b/v4/examples/asgi-gradio-interface.mdx
@@ -210,7 +210,7 @@ class GradioServer:
         interface.launch(
             server_name=self.host,
             server_port=self.port,
-            root_path=f"https://api.aws.us-east-1.cerebrium.ai/v4/{os.getenv('PROJECT_ID')}/{os.getenv('APP_NAME')}/",
+            root_path=f"https://api.cerebrium.ai/v4/{os.getenv('PROJECT_ID')}/{os.getenv('APP_NAME')}/",
             quiet=True
         )
 
@@ -350,7 +350,7 @@ class GradioServer:
         interface.launch(
             server_name=self.host,
             server_port=self.port,
-            root_path=f"https://api.aws.us-east-1.cerebrium.ai/v4/{os.getenv('PROJECT_ID')}/{os.getenv('APP_NAME')}/",
+            root_path=f"https://api.cerebrium.ai/v4/{os.getenv('PROJECT_ID')}/{os.getenv('APP_NAME')}/",
             quiet=True
         )
 
@@ -445,7 +445,7 @@ cerebrium deploy -y
 Once deployed, navigate to the following URL in your browser:
 
 ```
-https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR_PROJECT_ID>/2-gradio-interface/
+https://api.cerebrium.ai/v4/p-xxxxxxxx/2-gradio-interface/
 ```
 
 The Gradio chat interface appears at this URL.
diff --git a/v4/examples/comfyUI.mdx b/v4/examples/comfyUI.mdx
index 37c5bd7d..14e65596 100644
--- a/v4/examples/comfyUI.mdx
+++ b/v4/examples/comfyUI.mdx
@@ -343,7 +343,7 @@ Deploy the application: `cerebrium deploy`
 After successful deployment, make a request to the endpoint with the following JSON payload:
 
 ```curl
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxx/1-comfyui/run' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/1-comfyui/run' \
 --header 'Content-Type: application/json' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --data '{"workflow_values": {
diff --git a/v4/examples/deploy-a-vision-language-model-with-sglang.mdx b/v4/examples/deploy-a-vision-language-model-with-sglang.mdx
index b2016781..e28dc4eb 100644
--- a/v4/examples/deploy-a-vision-language-model-with-sglang.mdx
+++ b/v4/examples/deploy-a-vision-language-model-with-sglang.mdx
@@ -236,7 +236,7 @@ cerebrium deploy
 Once deployed, test with a sample request:
 
 ```bash
-curl -X POST "https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR-PROJECT-ID>/7-vision-language-sglang/analyze" \
+curl -X POST "https://api.cerebrium.ai/v4/p-xxxxxxxx/7-vision-language-sglang/analyze" \
   -H "Content-Type: application/json" \
   -d '{
     "company_description": "Nike is a global leader in athletic footwear, apparel, and sports equipment known for its innovative designs and the iconic “swoosh” logo. The brand embodies performance, style, and inspiration, empowering athletes worldwide to Just Do It."",
diff --git a/v4/examples/deploy-an-llm-with-tensorrtllm-tritonserver.mdx b/v4/examples/deploy-an-llm-with-tensorrtllm-tritonserver.mdx
index 2211e34a..6c7c27cb 100644
--- a/v4/examples/deploy-an-llm-with-tensorrtllm-tritonserver.mdx
+++ b/v4/examples/deploy-an-llm-with-tensorrtllm-tritonserver.mdx
@@ -452,7 +452,7 @@ After successful deployment, the base endpoint URL appears in the output. Use th
 Send a request to your deployed endpoint:
 
 ```bash
-curl -X POST https://api.aws.us-east-1.cerebrium.ai/v4/<project-id>/<name>/v2/models/llama3_2/infer \
+curl -X POST https://api.cerebrium.ai/v4/p-xxxxxxxx/<name>/v2/models/llama3_2/infer \
   -H "Content-Type: application/json" \
   -d '{
     "inputs": [
diff --git a/v4/examples/gpt-oss.mdx b/v4/examples/gpt-oss.mdx
index 0270e5dd..3d535b01 100644
--- a/v4/examples/gpt-oss.mdx
+++ b/v4/examples/gpt-oss.mdx
@@ -76,7 +76,7 @@ Deploy by running `cerebrium deploy`. The environment is created and the model i
 Test the endpoint with the following request:
 
 ```
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxx/7-openai-gpt-oss/v1/chat/completions' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/7-openai-gpt-oss/v1/chat/completions' \
 --header 'Content-Type: application/json' \
 --header 'Accept: text/event-stream' \
 --data '{"messages": [{"role": "user", "content": "hello how are you"}], "model": "Qwen/Qwen2.5-1.5B-Instruct", "stream": true}'
diff --git a/v4/examples/high-throughput-embeddings.mdx b/v4/examples/high-throughput-embeddings.mdx
index a66def93..6e4ffb30 100644
--- a/v4/examples/high-throughput-embeddings.mdx
+++ b/v4/examples/high-throughput-embeddings.mdx
@@ -202,7 +202,7 @@ Deploy with `cerebrium deploy`.
 After deployment, run inference with a command like:
 
 ```
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxx/infinity-throughput/image_embed' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/infinity-throughput/image_embed' \
 --header 'Content-Type: application/json' \
 --data '{"image_urls": ["https://www.borrowmydoggy.com/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2F4ij0poqn%2Fproduction%2Fe24bfbd855cda99e303975f2bd2a1bf43079b320-800x600.jpg&w=1080&q=80"]}'
 ```
diff --git a/v4/examples/langchain.mdx b/v4/examples/langchain.mdx
index 26151a9b..b60f3a8e 100644
--- a/v4/examples/langchain.mdx
+++ b/v4/examples/langchain.mdx
@@ -198,7 +198,7 @@ cerebrium deploy
 After deployment, make this request:
 
 ```curl
-curl --location --request POST 'https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxx/1-langchain-QA/predict' \
+curl --location --request POST 'https://api.cerebrium.ai/v4/p-xxxxxxxx/1-langchain-QA/predict' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --header 'Content-Type: application/json' \
 --data-raw '{
diff --git a/v4/examples/mistral-vllm.mdx b/v4/examples/mistral-vllm.mdx
index df1f5efe..293297c8 100644
--- a/v4/examples/mistral-vllm.mdx
+++ b/v4/examples/mistral-vllm.mdx
@@ -156,7 +156,7 @@ cerebrium deploy
 After deployment, make this request:
 
 ```curl
-curl --location --request POST 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/1-faster-inference-with-vllm/predict' \
+curl --location --request POST 'https://api.cerebrium.ai/v4/p-xxxxxxxx/1-faster-inference-with-vllm/predict' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --header 'Content-Type: application/json' \
 --data-raw '{
diff --git a/v4/examples/openai-compatible-endpoint-vllm.mdx b/v4/examples/openai-compatible-endpoint-vllm.mdx
index 292fbefe..8c0bb58a 100644
--- a/v4/examples/openai-compatible-endpoint-vllm.mdx
+++ b/v4/examples/openai-compatible-endpoint-vllm.mdx
@@ -117,7 +117,7 @@ cerebrium deploy
 After deployment, a curl command like this appears:
 
 ```curl
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/5-openai-compatible-endpoint/{function}' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/5-openai-compatible-endpoint/{function}' \
 --header 'Content-Type: application/json' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --data '{"..."}'
@@ -130,7 +130,7 @@ import os
 from openai import OpenAI
 
 client = OpenAI(
-    base_url="https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxxx/5-openai-compatible-endpoint/run",
+    base_url="https://api.cerebrium.ai/v4/p-xxxxxxxx/5-openai-compatible-endpoint/run",
     api_key="<CEREBRIUM_JWT_TOKEN>",
 )
 
diff --git a/v4/examples/realtime-voice-agents.mdx b/v4/examples/realtime-voice-agents.mdx
index 2b533260..493de3fa 100644
--- a/v4/examples/realtime-voice-agents.mdx
+++ b/v4/examples/realtime-voice-agents.mdx
@@ -467,7 +467,7 @@ A public fork of the PipeCat frontend demonstrates this application. Clone the r
 Follow the instructions in the README.md and then populate the following variables in your .env.development.local
 
 ```
-VITE_SERVER_URL=https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxx/<APP_NAME> #This is the base url of your pipecat-agent. Do not include the function names
+VITE_SERVER_URL=https://api.cerebrium.ai/v4/p-xxxxxxxx/<APP_NAME> #This is the base url of your pipecat-agent. Do not include the function names
 VITE_SERVER_AUTH= #This is the JWT token you can get from the API Keys section of your Cerebrium Dashboard.
 ```
 
diff --git a/v4/examples/sdxl.mdx b/v4/examples/sdxl.mdx
index 4a05677c..fcc0c82c 100644
--- a/v4/examples/sdxl.mdx
+++ b/v4/examples/sdxl.mdx
@@ -147,7 +147,7 @@ cerebrium deploy
 After deployment, make this request:
 
 ```curl
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/3-sdxl-refiner/predict' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/3-sdxl-refiner/predict' \
 --header 'Content-Type: application/json' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --data '{
diff --git a/v4/examples/streaming-falcon-7B.mdx b/v4/examples/streaming-falcon-7B.mdx
index 1b7b912b..b411a07a 100644
--- a/v4/examples/streaming-falcon-7B.mdx
+++ b/v4/examples/streaming-falcon-7B.mdx
@@ -184,7 +184,7 @@ After deployment, make this request:
 </Note>
 
 ```curl
-curl --location --request POST 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/5-streaming-endpoint/stream' \
+curl --location --request POST 'https://api.cerebrium.ai/v4/p-xxxxxxxx/5-streaming-endpoint/stream' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --header 'Content-Type: application/json' \
 --data-raw '{
diff --git a/v4/examples/transcribe-whisper.mdx b/v4/examples/transcribe-whisper.mdx
index 01d7b609..6b0a230b 100644
--- a/v4/examples/transcribe-whisper.mdx
+++ b/v4/examples/transcribe-whisper.mdx
@@ -146,7 +146,7 @@ cerebrium deploy
 After deployment, make this request:
 
 ```curl
-curl --location 'https://api.aws.us-east-1.cerebrium.ai/v4/p-<YOUR PROJECT ID>/1-whisper-transcription/predict' \
+curl --location 'https://api.cerebrium.ai/v4/p-xxxxxxxx/1-whisper-transcription/predict' \
 --header 'Content-Type: application/json' \
 --header 'Authorization: Bearer <YOUR TOKEN HERE>' \
 --data '{"file_url": "https://your-public-url.com/test.mp3"}''
diff --git a/v4/examples/twilio-voice-agent.mdx b/v4/examples/twilio-voice-agent.mdx
index c1db2434..3f12338b 100644
--- a/v4/examples/twilio-voice-agent.mdx
+++ b/v4/examples/twilio-voice-agent.mdx
@@ -88,7 +88,7 @@ Create a `templates` folder with `stream.xml` inside. This XML response tells Tw
 <Response>
   <Connect>
     <!--Update with your project ID below-->
-    <Stream url="wss://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxxx/4-twilio-agent/ws"></Stream>
+    <Stream url="wss://api.cerebrium.ai/v4/p-xxxxxxxx/4-twilio-agent/ws"></Stream>
   </Connect>
   <Pause length="40"/>
 </Response>
diff --git a/v4/examples/wandb-sweep.mdx b/v4/examples/wandb-sweep.mdx
index e8c22145..bfc49bf6 100644
--- a/v4/examples/wandb-sweep.mdx
+++ b/v4/examples/wandb-sweep.mdx
@@ -322,7 +322,7 @@ from dotenv import load_dotenv
 load_dotenv()
 
 CEREBRIUM_API_KEY = os.getenv("CEREBRIUM_API_KEY")
-ENDPOINT_URL = "https://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxx/wandb-sweep/train_model?async=true"
+ENDPOINT_URL = "https://api.cerebrium.ai/v4/p-xxxxxxxx/wandb-sweep/train_model?async=true"
 
 def train_with_params(params: Dict[str, Any]):
     """