Overview:
The system will enable processing of an MP3 file stored in Salesforce, extract its text content using AWS Lambda, analyze it with Amazon Comprehend to identify PII (Personally Identifiable Information) and PHI (Protected Health Information), and alert relevant stakeholders based on findings.
High-Level Design Steps:
1. Salesforce Setup:
• Object Storage: Store MP3 files in Salesforce (e.g., on a custom object or standard object with a ContentDocument or File relationship).
• Trigger/Flow: Create a trigger or Flow in Salesforce that initiates the process upon the upload of an MP3 file.
• AWS Integration Point: Configure a callout to AWS Lambda using an Apex class or Platform Event.
2. AWS Lambda Setup:
• Input: Receive the MP3 file from Salesforce.
• Processing:
• Use Amazon Transcribe to convert the MP3 file into text.
• Pass the transcribed text to Amazon Comprehend.
• Output: Return PII/PHI analysis results back to Salesforce or trigger an alert.
3. Amazon Comprehend Analysis:
• Enable Amazon Comprehend’s PII/PHI detection features.
• Analyze the transcribed text to identify sensitive information.
• Return identified data categories and severity levels (if applicable).
4. Alerting System:
• Salesforce Notification: Update the original record with analysis results or flag it.
• Email/SMS Alerts: Trigger email or SMS notifications using Salesforce capabilities (e.g., email alerts or integration with an SMS provider).
Detailed Design:
1. Salesforce Configuration:
• Custom Fields:
• File Reference: To link the MP3 file.
• Analysis Status: (Pending, In Progress, Completed, Flagged).
• PII/PHI Summary: To store the analysis results.
• Apex Callout Class:
• Use Salesforce’s HttpRequest to send the file to AWS Lambda.
• Example Apex class:
public class AWSFileProcessor {
@Future(callout=true)
public static void sendToAWS(Id contentDocumentId) {
ContentVersion contentVersion = [
SELECT VersionData, Title
FROM ContentVersion
WHERE ContentDocumentId = :contentDocumentId
LIMIT 1
];
HttpRequest req = new HttpRequest();
req.setEndpoint(‘AWS_LAMBDA_ENDPOINT_URL’);
req.setMethod(‘POST’);
req.setHeader(‘Content-Type’, ‘multipart/form-data’);
req.setBodyBlob(contentVersion.VersionData);
Http http = new Http();
HttpResponse res = http.send(req);
// Handle Response Logic (e.g., update analysis status).
}
}
• Trigger/Flow:
• On MP3 upload, invoke AWSFileProcessor.sendToAWS().
2. AWS Lambda Function:
• Lambda Trigger: HTTPS endpoint using API Gateway.
• Steps:
1. Receive File:
• Parse incoming request to retrieve the MP3 file.
2. Transcribe:
• Use boto3 to call Amazon Transcribe:
import boto3
transcribe = boto3.client(‘transcribe’)
response = transcribe.start_transcription_job(
TranscriptionJobName=’YourJobName’,
Media={‘MediaFileUri’: ‘s3://your-bucket/file.mp3’},
MediaFormat=’mp3′,
LanguageCode=’en-US’
)
• Retrieve the transcription text once complete.
3. Comprehend Analysis:
• Pass the transcribed text to Amazon Comprehend for PII/PHI analysis:
comprehend = boto3.client(‘comprehend’)
response = comprehend.detect_pii_entities(
Text=transcribed_text,
LanguageCode=’en’
)
4. Return Results:
• Send the PII/PHI analysis results (e.g., detected entities and confidence scores) back to Salesforce.
3. Salesforce Update:
• Process Results:
• Parse the Lambda response and update the Salesforce record:
• Update Analysis Status to Completed or Flagged.
• Store a summary of PII/PHI data in the record.
• Trigger Alerts:
• If sensitive data is detected, trigger Salesforce email alerts or notify stakeholders.
4. AWS Comprehend Configuration:
• Enable Amazon Comprehend’s PII/PHI detection capabilities in the AWS Management Console.
• Ensure necessary IAM roles and permissions for Lambda to use Amazon Transcribe and Comprehend.
Sequence Diagram:
1. File Upload: User uploads MP3 file in Salesforce.
2. Trigger: Salesforce sends MP3 file to AWS Lambda.
3. Processing:
• Lambda uses Amazon Transcribe to convert audio to text.
• Transcribed text is analyzed by Amazon Comprehend for PII/PHI data.
4. Results Returned: Lambda sends results back to Salesforce.
5. Alert: Salesforce updates record and triggers notifications if sensitive data is detected.
Error Handling:
1. AWS Errors:
• Log errors in Salesforce (e.g., failed transcription or analysis).
• Retry logic in Lambda for transient issues.
2. Salesforce Errors:
• Ensure appropriate exception handling in Apex code.
Benefits:
• Fully automated detection and alerting system.
• Efficient use of AWS services for transcription and analysis.
• Seamless integration with Salesforce for alerting and monitoring.
Below are examples of both the Apex code for Salesforce and the Python code for AWS Lambda that implements the design.
Apex Code (Salesforce)
Apex Class: AWSFileProcessor
This class handles the callout to AWS Lambda to send the MP3 file.
public class AWSFileProcessor {
@Future(callout=true)
public static void sendToAWS(Id contentDocumentId) {
try {
// Fetch the file data
ContentVersion contentVersion = [
SELECT VersionData, Title
FROM ContentVersion
WHERE ContentDocumentId = :contentDocumentId
LIMIT 1
];
// Create HTTP Request
HttpRequest req = new HttpRequest();
req.setEndpoint(‘https://your-lambda-endpoint.amazonaws.com/’); // Replace with your Lambda endpoint
req.setMethod(‘POST’);
req.setHeader(‘Content-Type’, ‘application/json’);
// Convert file data to Base64
String base64File = EncodingUtil.base64Encode(contentVersion.VersionData);
// Request Body
Map<String, Object> requestBody = new Map<String, Object>{
‘fileName’ => contentVersion.Title,
‘fileData’ => base64File
};
req.setBody(JSON.serialize(requestBody));
// Send Request
Http http = new Http();
HttpResponse res = http.send(req);
// Process Response
if (res.getStatusCode() == 200) {
System.debug(‘Response: ‘ + res.getBody());
// Update record or process results further if needed
} else {
System.debug(‘Error: ‘ + res.getBody());
}
} catch (Exception e) {
System.debug(‘Exception: ‘ + e.getMessage());
}
}
}
Trigger Example
Trigger to call AWSFileProcessor.sendToAWS() when a new file is uploaded.
trigger FileUploadTrigger on ContentDocument (after insert) {
for (ContentDocument doc : Trigger.new) {
AWSFileProcessor.sendToAWS(doc.Id);
}
}
Python Code (AWS Lambda)
Lambda Function
This function receives the MP3 file, processes it with Amazon Transcribe, and analyzes the transcription with Amazon Comprehend.
import json
import boto3
import base64
import logging
import uuid
# Initialize AWS Clients
s3 = boto3.client(‘s3’)
transcribe = boto3.client(‘transcribe’)
comprehend = boto3.client(‘comprehend’)
# Configure Logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def lambda_handler(event, context):
try:
# Parse Incoming Request
body = json.loads(event[‘body’])
file_name = body[‘fileName’]
file_data = base64.b64decode(body[‘fileData’])
# Upload File to S3
s3_bucket = ‘your-s3-bucket-name’ # Replace with your S3 bucket name
s3_key = f’transcribe/{uuid.uuid4()}_{file_name}’
s3.put_object(Bucket=s3_bucket, Key=s3_key, Body=file_data)
# Start Transcription Job
transcribe_job_name = f’TranscribeJob-{uuid.uuid4()}’
transcribe.start_transcription_job(
TranscriptionJobName=transcribe_job_name,
Media={‘MediaFileUri’: f’s3://{s3_bucket}/{s3_key}’},
MediaFormat=’mp3′,
LanguageCode=’en-US’,
OutputBucketName=s3_bucket
)
# Wait for Transcription Job to Complete
while True:
job_status = transcribe.get_transcription_job(TranscriptionJobName=transcribe_job_name)
if job_status[‘TranscriptionJob’][‘TranscriptionJobStatus’] in [‘COMPLETED’, ‘FAILED’]:
break
if job_status[‘TranscriptionJob’][‘TranscriptionJobStatus’] == ‘FAILED’:
raise Exception(‘Transcription job failed.’)
# Fetch Transcribed Text
transcription_uri = job_status[‘TranscriptionJob’][‘Transcript’][‘TranscriptFileUri’]
transcription_response = boto3.client(‘s3’).get_object(Bucket=s3_bucket, Key=transcription_uri.split(‘/’)[-1])
transcription_data = json.loads(transcription_response[‘Body’].read())
transcribed_text = transcription_data[‘results’][‘transcripts’][0][‘transcript’]
# Analyze with Amazon Comprehend
comprehend_response = comprehend.detect_pii_entities(
Text=transcribed_text,
LanguageCode=’en’
)
# Return Results
return {
‘statusCode’: 200,
‘body’: json.dumps({
‘transcribedText’: transcribed_text,
‘piiEntities’: comprehend_response[‘Entities’]
})
}
except Exception as e:
logger.error(f”Error: {str(e)}”)
return {
‘statusCode’: 500,
‘body’: json.dumps({‘error’: str(e)})
}
Deployment Notes:
1. Apex Class:
• Replace https://your-lambda-endpoint.amazonaws.com/ with your actual Lambda API Gateway endpoint.
• Ensure that the necessary permissions are granted in Salesforce for callouts.
2. AWS Lambda:
• Replace your-s3-bucket-name with your actual S3 bucket.
• Ensure the Lambda function has necessary IAM permissions to access S3, Transcribe, and Comprehend.
3. Testing:
• Test with various MP3 files to ensure the transcription and analysis pipelines work seamlessly.
• Validate error handling for edge cases like unsupported file formats or missing data.
SalesforceTen.com 
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