diff --git a/docs/my-website/docs/tutorials/presidio_pii_masking.md b/docs/my-website/docs/tutorials/presidio_pii_masking.md
new file mode 100644
index 00000000000..9f75201fb93
--- /dev/null
+++ b/docs/my-website/docs/tutorials/presidio_pii_masking.md
@@ -0,0 +1,684 @@
+import Image from '@theme/IdealImage';
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# Presidio PII Masking with LiteLLM - Complete Tutorial
+
+This tutorial will guide you through setting up PII (Personally Identifiable Information) masking with Microsoft Presidio and LiteLLM Gateway. By the end of this tutorial, you'll have a production-ready setup that automatically detects and masks sensitive information in your LLM requests.
+
+## What You'll Learn
+
+- Deploy Presidio containers for PII detection
+- Configure LiteLLM to automatically mask sensitive data
+- Test PII masking with real examples
+- Monitor and trace guardrail execution
+- Configure advanced features like output parsing and language support
+
+## Why Use PII Masking?
+
+When working with LLMs, users may inadvertently share sensitive information like:
+- Credit card numbers
+- Email addresses
+- Phone numbers
+- Social Security Numbers
+- Medical information (PHI)
+- Personal names and addresses
+
+PII masking automatically detects and redacts this information before it reaches the LLM, protecting user privacy and helping you comply with regulations like GDPR, HIPAA, and CCPA.
+
+## Prerequisites
+
+Before starting this tutorial, ensure you have:
+- Docker installed on your machine
+- A LiteLLM API key or OpenAI API key for testing
+- Basic familiarity with YAML configuration
+- `curl` or a similar HTTP client for testing
+
+## Part 1: Deploy Presidio Containers
+
+Presidio consists of two main services:
+1. **Presidio Analyzer**: Detects PII in text
+2. **Presidio Anonymizer**: Masks or redacts the detected PII
+
+### Step 1.1: Deploy with Docker
+
+Create a `docker-compose.yml` file for Presidio:
+
+```yaml
+version: '3.8'
+
+services:
+  presidio-analyzer:
+    image: mcr.microsoft.com/presidio-analyzer:latest
+    ports:
+      - "5002:5002"
+    environment:
+      - GRPC_PORT=5001
+    networks:
+      - presidio-network
+
+  presidio-anonymizer:
+    image: mcr.microsoft.com/presidio-anonymizer:latest
+    ports:
+      - "5001:5001"
+    networks:
+      - presidio-network
+
+networks:
+  presidio-network:
+    driver: bridge
+```
+
+### Step 1.2: Start the Containers
+
+```bash
+docker-compose up -d
+```
+
+### Step 1.3: Verify Presidio is Running
+
+Test the analyzer endpoint:
+
+```bash
+curl -X POST http://localhost:5002/analyze \
+  -H "Content-Type: application/json" \
+  -d '{
+    "text": "My email is john.doe@example.com",
+    "language": "en"
+  }'
+```
+
+You should see a response like:
+
+```json
+[
+  {
+    "entity_type": "EMAIL_ADDRESS",
+    "start": 12,
+    "end": 33,
+    "score": 1.0
+  }
+]
+```
+
+✅ **Checkpoint**: Your Presidio containers are now running and ready!
+
+## Part 2: Configure LiteLLM Gateway
+
+Now let's configure LiteLLM to use Presidio for automatic PII masking.
+
+### Step 2.1: Create LiteLLM Configuration
+
+Create a `config.yaml` file:
+
+```yaml
+model_list:
+  - model_name: gpt-3.5-turbo
+    litellm_params:
+      model: openai/gpt-3.5-turbo
+      api_key: os.environ/OPENAI_API_KEY
+
+guardrails:
+  - guardrail_name: "presidio-pii-guard"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"  # Run before LLM call
+      pii_entities_config:
+        CREDIT_CARD: "MASK"
+        EMAIL_ADDRESS: "MASK"
+        PHONE_NUMBER: "MASK"
+        PERSON: "MASK"
+        US_SSN: "MASK"
+```
+
+### Step 2.2: Set Environment Variables
+
+```bash
+export OPENAI_API_KEY="your-openai-key"
+export PRESIDIO_ANALYZER_API_BASE="http://localhost:5002"
+export PRESIDIO_ANONYMIZER_API_BASE="http://localhost:5001"
+```
+
+### Step 2.3: Start LiteLLM Gateway
+
+```bash
+litellm --config config.yaml --port 4000 --detailed_debug
+```
+
+You should see output indicating the guardrails are loaded:
+
+```
+Loaded guardrails: ['presidio-pii-guard']
+```
+
+✅ **Checkpoint**: LiteLLM Gateway is running with PII masking enabled!
+
+## Part 3: Test PII Masking
+
+Let's test the PII masking with various types of sensitive data.
+
+### Test 1: Basic PII Detection
+
+<Tabs>
+<TabItem label="Request with PII" value="pii-request">
+
+```bash
+curl -X POST http://localhost:4000/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {
+        "role": "user",
+        "content": "My name is John Smith, my email is john.smith@example.com, and my credit card is 4111-1111-1111-1111"
+      }
+    ],
+    "guardrails": ["presidio-pii-guard"]
+  }'
+```
+
+</TabItem>
+
+<TabItem label="What LLM Receives" value="masked">
+
+The LLM will receive the masked version:
+
+```
+My name is <PERSON>, my email is <EMAIL_ADDRESS>, and my credit card is <CREDIT_CARD>
+```
+
+</TabItem>
+
+<TabItem label="Response" value="response">
+
+```json
+{
+  "id": "chatcmpl-123abc",
+  "choices": [
+    {
+      "message": {
+        "content": "I can see you've provided some information. However, I noticed some sensitive data placeholders. For security reasons, I recommend not sharing actual personal information like credit card numbers.",
+        "role": "assistant"
+      },
+      "finish_reason": "stop"
+    }
+  ],
+  "model": "gpt-3.5-turbo"
+}
+```
+
+</TabItem>
+</Tabs>
+
+### Test 2: Medical Information (PHI)
+
+```bash
+curl -X POST http://localhost:4000/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {
+        "role": "user",
+        "content": "Patient Jane Doe, DOB 01/15/1980, MRN 123456, presents with symptoms of fever."
+      }
+    ],
+    "guardrails": ["presidio-pii-guard"]
+  }'
+```
+
+The patient name and medical record number will be automatically masked.
+
+### Test 3: No PII (Normal Request)
+
+```bash
+curl -X POST http://localhost:4000/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {
+        "role": "user",
+        "content": "What is the capital of France?"
+      }
+    ],
+    "guardrails": ["presidio-pii-guard"]
+  }'
+```
+
+This request passes through unchanged since there's no PII detected.
+
+✅ **Checkpoint**: You've successfully tested PII masking!
+
+## Part 4: Advanced Configurations
+
+### Blocking Sensitive Entities
+
+Instead of masking, you can completely block requests containing specific PII types:
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-block-guard"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"
+      pii_entities_config:
+        US_SSN: "BLOCK"  # Block any request with SSN
+        CREDIT_CARD: "BLOCK"  # Block credit card numbers
+        MEDICAL_LICENSE: "BLOCK"
+```
+
+Test the blocking behavior:
+
+```bash
+curl -X POST http://localhost:4000/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {"role": "user", "content": "My SSN is 123-45-6789"}
+    ],
+    "guardrails": ["presidio-block-guard"]
+  }'
+```
+
+Expected response:
+
+```json
+{
+  "error": {
+    "message": "Blocked PII entity detected: US_SSN by Guardrail: presidio-block-guard."
+  }
+}
+```
+
+### Output Parsing (Unmasking)
+
+Enable output parsing to automatically replace masked tokens in LLM responses with original values:
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-output-parse"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"
+      output_parse_pii: true  # Enable output parsing
+      pii_entities_config:
+        PERSON: "MASK"
+        PHONE_NUMBER: "MASK"
+```
+
+**How it works:**
+
+1. **User Input**: "Hello, my name is Jane Doe. My number is 555-1234"
+2. **LLM Receives**: "Hello, my name is `<PERSON>`. My number is `<PHONE_NUMBER>`"
+3. **LLM Response**: "Nice to meet you, `<PERSON>`!"
+4. **User Receives**: "Nice to meet you, Jane Doe!" ✨
+
+### Multi-language Support
+
+Configure PII detection for different languages:
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-spanish"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"
+      presidio_language: "es"  # Spanish
+      pii_entities_config:
+        CREDIT_CARD: "MASK"
+        PERSON: "MASK"
+        
+  - guardrail_name: "presidio-german"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"
+      presidio_language: "de"  # German
+      pii_entities_config:
+        CREDIT_CARD: "MASK"
+        PERSON: "MASK"
+```
+
+You can also override language per request:
+
+```bash
+curl -X POST http://localhost:4000/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {"role": "user", "content": "Mi tarjeta de crédito es 4111-1111-1111-1111"}
+    ],
+    "guardrails": ["presidio-spanish"],
+    "guardrail_config": {"language": "fr"}
+  }'
+```
+
+### Logging-Only Mode
+
+Apply PII masking only to logs (not to actual LLM requests):
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-logging"
+    litellm_params:
+      guardrail: presidio
+      mode: "logging_only"  # Only mask in logs
+      pii_entities_config:
+        CREDIT_CARD: "MASK"
+        EMAIL_ADDRESS: "MASK"
+```
+
+This is useful when:
+- You want to allow PII in production requests
+- But need to comply with logging regulations
+- Integrating with Langfuse, Datadog, etc.
+
+## Part 5: Monitoring and Tracing
+
+### View Guardrail Execution on LiteLLM UI
+
+If you're using the LiteLLM Admin UI, you can see detailed guardrail traces:
+
+1. Navigate to the **Logs** page
+2. Click on any request that used the guardrail
+3. View detailed information:
+   - Which entities were detected
+   - Confidence scores for each detection
+   - Guardrail execution duration
+   - Original vs. masked content
+
+<Image 
+  img={require('../../img/presidio_4.png')}
+  style={{width: '60%', display: 'block', margin: '0'}}
+/>
+
+### Integration with Langfuse
+
+If you're logging to Langfuse, guardrail information is automatically included:
+
+```yaml
+litellm_settings:
+  success_callback: ["langfuse"]
+
+environment_variables:
+  LANGFUSE_PUBLIC_KEY: "your-public-key"
+  LANGFUSE_SECRET_KEY: "your-secret-key"
+```
+
+<Image 
+  img={require('../../img/presidio_5.png')}
+  style={{width: '60%', display: 'block', margin: '0'}}
+/>
+
+### Programmatic Access to Guardrail Metadata
+
+You can access guardrail metadata in custom callbacks:
+
+```python
+import litellm
+
+def custom_callback(kwargs, result, **callback_kwargs):
+    # Access guardrail metadata
+    metadata = kwargs.get("metadata", {})
+    guardrail_results = metadata.get("guardrails", {})
+    
+    print(f"Masked entities: {guardrail_results}")
+    
+litellm.callbacks = [custom_callback]
+```
+
+## Part 6: Production Best Practices
+
+### 1. Performance Optimization
+
+**Use parallel execution for pre-call guardrails:**
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-guard"
+    litellm_params:
+      guardrail: presidio
+      mode: "during_call"  # Runs in parallel with LLM call
+```
+
+### 2. Configure Entity Types by Use Case
+
+**Healthcare Application:**
+
+```yaml
+pii_entities_config:
+  PERSON: "MASK"
+  MEDICAL_LICENSE: "BLOCK"
+  US_SSN: "BLOCK"
+  PHONE_NUMBER: "MASK"
+  EMAIL_ADDRESS: "MASK"
+  DATE_TIME: "MASK"  # May contain appointment dates
+```
+
+**Financial Application:**
+
+```yaml
+pii_entities_config:
+  CREDIT_CARD: "BLOCK"
+  US_BANK_NUMBER: "BLOCK"
+  US_SSN: "BLOCK"
+  PHONE_NUMBER: "MASK"
+  EMAIL_ADDRESS: "MASK"
+  PERSON: "MASK"
+```
+
+**Customer Support Application:**
+
+```yaml
+pii_entities_config:
+  EMAIL_ADDRESS: "MASK"
+  PHONE_NUMBER: "MASK"
+  PERSON: "MASK"
+  CREDIT_CARD: "BLOCK"  # Should never be shared
+```
+
+### 3. High Availability Setup
+
+For production deployments, run multiple Presidio instances:
+
+```yaml
+version: '3.8'
+
+services:
+  presidio-analyzer-1:
+    image: mcr.microsoft.com/presidio-analyzer:latest
+    ports:
+      - "5002:5002"
+    deploy:
+      replicas: 3
+      
+  presidio-anonymizer-1:
+    image: mcr.microsoft.com/presidio-anonymizer:latest
+    ports:
+      - "5001:5001"
+    deploy:
+      replicas: 3
+```
+
+Use a load balancer (nginx, HAProxy) to distribute requests.
+
+### 4. Custom Entity Recognition
+
+For domain-specific PII (e.g., internal employee IDs), create custom recognizers:
+
+Create `custom_recognizers.json`:
+
+```json
+[
+  {
+    "supported_language": "en",
+    "supported_entity": "EMPLOYEE_ID",
+    "patterns": [
+      {
+        "name": "employee_id_pattern",
+        "regex": "EMP-[0-9]{6}",
+        "score": 0.9
+      }
+    ]
+  }
+]
+```
+
+Configure in LiteLLM:
+
+```yaml
+guardrails:
+  - guardrail_name: "presidio-custom"
+    litellm_params:
+      guardrail: presidio
+      mode: "pre_call"
+      presidio_ad_hoc_recognizers: "./custom_recognizers.json"
+      pii_entities_config:
+        EMPLOYEE_ID: "MASK"
+```
+
+### 5. Testing Strategy
+
+Create test cases for your PII masking:
+
+```python
+import pytest
+from litellm import completion
+
+def test_pii_masking_credit_card():
+    """Test that credit cards are properly masked"""
+    response = completion(
+        model="gpt-3.5-turbo",
+        messages=[{
+            "role": "user",
+            "content": "My card is 4111-1111-1111-1111"
+        }],
+        api_base="http://localhost:4000",
+        metadata={
+            "guardrails": ["presidio-pii-guard"]
+        }
+    )
+    
+    # Verify the card number was masked
+    metadata = response.get("_hidden_params", {}).get("metadata", {})
+    assert "CREDIT_CARD" in str(metadata.get("guardrails", {}))
+
+def test_pii_masking_allows_normal_text():
+    """Test that normal text passes through"""
+    response = completion(
+        model="gpt-3.5-turbo",
+        messages=[{
+            "role": "user",
+            "content": "What is the weather today?"
+        }],
+        api_base="http://localhost:4000",
+        metadata={
+            "guardrails": ["presidio-pii-guard"]
+        }
+    )
+    
+    assert response.choices[0].message.content is not None
+```
+
+## Part 7: Troubleshooting
+
+### Issue: Presidio Not Detecting PII
+
+**Check 1: Language Configuration**
+
+```bash
+# Verify language is set correctly
+curl -X POST http://localhost:5002/analyze \
+  -H "Content-Type: application/json" \
+  -d '{
+    "text": "Meine E-Mail ist test@example.de",
+    "language": "de"
+  }'
+```
+
+**Check 2: Entity Types**
+
+Ensure the entity types you're looking for are in your config:
+
+```yaml
+pii_entities_config:
+  CREDIT_CARD: "MASK"
+  # Add all entity types you need
+```
+
+[View all supported entity types](https://microsoft.github.io/presidio/supported_entities/)
+
+### Issue: Presidio Containers Not Starting
+
+**Check logs:**
+
+```bash
+docker-compose logs presidio-analyzer
+docker-compose logs presidio-anonymizer
+```
+
+**Common issues:**
+- Port conflicts (5001, 5002 already in use)
+- Insufficient memory allocation
+- Docker network issues
+
+### Issue: High Latency
+
+**Solution 1: Use `during_call` mode**
+
+```yaml
+mode: "during_call"  # Runs in parallel
+```
+
+**Solution 2: Scale Presidio containers**
+
+```yaml
+deploy:
+  replicas: 3
+```
+
+**Solution 3: Enable caching**
+
+```yaml
+litellm_settings:
+  cache: true
+  cache_params:
+    type: "redis"
+```
+
+## Conclusion
+
+Congratulations! 🎉 You've successfully set up PII masking with Presidio and LiteLLM. You now have:
+
+✅ A production-ready PII masking solution  
+✅ Automatic detection of sensitive information  
+✅ Multiple configuration options (masking vs. blocking)  
+✅ Monitoring and tracing capabilities  
+✅ Multi-language support  
+✅ Best practices for production deployment  
+
+## Next Steps
+
+- **[View all supported PII entity types](https://microsoft.github.io/presidio/supported_entities/)**
+- **[Explore other LiteLLM guardrails](../proxy/guardrails/quick_start)**
+- **[Set up multiple guardrails](../proxy/guardrails/quick_start#combining-multiple-guardrails)**
+- **[Configure per-key guardrails](../proxy/virtual_keys#guardrails)**
+- **[Learn about custom guardrails](../proxy/guardrails/custom_guardrail)**
+
+## Additional Resources
+
+- [Presidio Documentation](https://microsoft.github.io/presidio/)
+- [LiteLLM Guardrails Reference](../proxy/guardrails/pii_masking_v2)
+- [LiteLLM GitHub Repository](https://github.com/BerriAI/litellm)
+- [Report Issues](https://github.com/BerriAI/litellm/issues)
+
+---
+
+**Need help?** Join our [Discord community](https://discord.com/invite/wuPM9dRgDw) or open an issue on GitHub!
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index 4a8b6bb2283..7f8a46b409e 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -730,6 +730,7 @@ const sidebars = {
         "tutorials/prompt_caching",
         "tutorials/tag_management",
         'tutorials/litellm_proxy_aporia',
+        "tutorials/presidio_pii_masking",
         "tutorials/elasticsearch_logging",
         "tutorials/gemini_realtime_with_audio",
         "tutorials/claude_responses_api",