Philterd

Talk to the Team

Tell us about your stack and the privacy problems you're trying to solve. We typically respond within one business day.

Prefer email? support@philterd.ai

Prefer to skip the form? Pick a time on our calendar →
or send a message

Please do not enter PII or PHI in this form. If you need to share an example, use a sanitized one.

Reference and how-to

Guides

Maintained guides to PII redaction with the Philterd toolkit: how redaction policies work, how to author them, and how the pieces fit together.

Integrations

Apache NiFi and Philter

How to use Philter to redact PII and PHI inside an Apache NiFi data flow, either through Philter's API or with an embedded NiFi processor.

Operations

Monitoring Philter in AWS

How to monitor a Philter deployment in AWS: application logs with CloudWatch Logs, availability via load balancer health checks, and metrics with CloudWatch Metrics.

AI privacy

PII in Vector Embeddings: A Defense Guide

Embeddings look like 'just numbers,' but recent research shows they're partially invertible. A practical defense guide for teams running vector stores against PII recovery attacks.

Fundamentals

PII vs PHI vs NPPI: An Engineer's Guide

Three acronyms that get used interchangeably and shouldn't be. A short, definitional reference for engineers and compliance leads, with the regulatory framework and the architectural implication for each.

Integrations

Redacting Text in Amazon Kinesis Data Firehose

Amazon Kinesis Firehose is a managed streaming service designed to take large amounts of data from one place to another. For example, you can take data from sources such as Amazon CloudWatch, AWS IoT, and custom applications using the AWS SDK to destinations Amazon S3, Amazon Redshift, Amazon Elasticsearch, and other services. In this post…

Operations

Referential Integrity with Valkey

How to configure a Valkey cache so Philter maintains referential integrity (consistent replacement values) across documents and contexts in a cluster.

File formats

The Hidden Difficulties of Redacting PDF Documents

PDFs leak redacted text in ways most people don't anticipate: invisible text layers, embedded files, attached portfolios, metadata, the works. A deep dive into why PDF redaction is harder than it looks, with famous failures and Philter's approach.

Policy authoring

The Phileas redaction policy schema

What a redaction policy is, how the JSON schema is structured, and how to use it to control exactly which PII is detected and how each type is redacted.

Detection

Using an LLM or Pattern-based Rules for PII/PHI Redaction

In our data-driven world, being able to protect Personally Identifiable Information (PII) and Protected Health Information (PHI) is imperative. Whether you’re securing customer data, complying with regulations like GDPR or HIPAA, or simply aiming for responsible data handling, the need to effectively redact sensitive information is crucial. Today, there are two primary approaches: leveraging the…

Fundamentals

What is Data Redaction? A Practical Guide

Data redaction is the process of removing sensitive information from documents and datasets, but the term covers more techniques than most people realize. A practical guide to the strategies, the trade-offs, and how to pick the right approach.

Encryption

What is format-preserving encryption?

Format-preserving encryption (FPE) encrypts a value so the ciphertext looks like the same kind of value (same length, same character set) without breaking downstream systems that expect that shape. A practical guide with credit-card examples for Phileas and Philter.

Policy authoring

Writing your first redaction policy

A hands-on walkthrough from an empty file to a working redaction policy: detect an entity, apply it with Philter, change how it redacts, and handle false positives.