About
Philterd is the open source company behind self-hosted PII and PHI redaction for healthcare, finance, legal, government, and AI workloads. We build the software, maintain the models, and support the deployments.
Founder
Jeff founded Philterd and built Philter and the open source toolkit around it, so teams can redact sensitive data inside their own environments.
He is on the Apache OpenNLP project management committee and a member of the Apache Software Foundation, with 25+ years in software engineering, search, NLP, and data privacy.
Jeff leads every Philterd engagement, so you work directly with the person who wrote the code.
Philterd was founded by Jeff Zemerick after watching commercial privacy tools turn into proprietary black boxes: APIs that required sending sensitive data to the cloud just to redact it. We believed there was a better way.
We started by building Phileas as an open source library: auditable, embeddable, and free for anyone to use. It was the proof that privacy software didn't have to be opaque. The library quickly grew into the engine behind Philter, the enterprise-grade redaction API used today by healthcare, legal, and financial organizations.
In July 2024 we released Philter itself under the Apache License 2.0, and Philter 3.0 followed in November. PhEye, the service that hosts our PII detection models, was released in September.
The toolkit grew past the API: Philter Workspace for human review of redactions and PhiSQL for declarative PII operations in May, and Philter Desktop for redacting documents on a Windows PC in July.
Philter 4.0 made Philter an API-only service that stores its own data and records a tamper-evident ledger of what it redacted.
Philter One is a small computer for your office, coming soon, that arrives set up with Philter and Philter Workspace, so a person signs off on every document before a redacted copy is made.
Philter and the rest of the Philterd toolkit run inside your own environment, whether that is your cloud, your own servers, or your desktop. Your data stays in your perimeter, never reaches a third-party API, and never lands in someone else's logs.
Transparency is the only way to verify privacy software. Our core engine is Apache 2.0 licensed, so your engineers can read every line, audit every decision, and extend the stack on their own terms.
Generic LLMs make poor privacy filters. We train and ship specialized NLP and deep-learning models built specifically for PII and PHI detection. They are tunable, measured against precision and recall, and operationally affordable at scale.
Work directly with the creators of Philter to design and deploy PII redaction systems for your stack.
Learn about consultingAsk questions, report bugs, share redaction policies, and connect with other Philterd users on GitHub.
Join the communityHave a question or want to discuss a project? Reach out and we will get back to you within one business day.
Send a messageEvaluating Philterd? Download the solution brief (PDF).
Webinars, office hours, and live demos are listed on the Events page when they are scheduled.
Interested in working with us? Send your resume to careers@philterd.ai.
