Philter® Solution Gallery
This is a collection of example solutions built with Philter to find and remove sensitive information from text. You are welcome to copy these solutions and tailor them to your use-cases and challenges.
Filtering Sensitive Information in an Apache NiFi Data Flow
Topics: Data in motion, streaming text, data flow, Apache NiFi
Required Coding: None
Use Philter with Apache NiFi to remove sensitive information from text in your data flow. Philter can process the content of flowfiles to redact sensitive information without requiring any custom NiFi processors or code.
Using AWS Kinesis Firehose Transformations to Filter Sensitive Information from Streaming Text
Topics: Data in motion, streaming text, data flow, AWS, Kinesis, Lambda
Required Coding: Python
Use Philter to find and remove sensitive information from text inside an AWS Kinesis Firehose stream. Use a Transformation Lambda function to execute Philter on the streaming text.
Using Philter with Microsoft Power Automate
Topics: Data in motion, streaming text, data flow, Microsoft Power Automate
Required Coding: None
Use Philter to find and remove sensitive information from text inside a Microsoft Power Automate flow. Using an HTTP step, we can integrate Philter with our flow to filter text.
