Healthcare automation gets valuable the moment it gets sensitive.
Privent runs as a native node inside your n8n workflows. It detects and tokenizes patient data before an external model ever sees it, then restores the original values only at the healthcare systems you trust.
The workflows that save the most staff time are usually the ones that touch the most sensitive data first. An n8n intake agent might pull a patient's contact details, symptoms, insurance information, and clinician notes into a single prompt before it asks a model to summarize the case or route it to the right queue. That is genuinely useful automation, and it is also the exact moment a routine workflow turns into a data control problem.
Most security tooling only sees the request that finally leaves the network. It never sees the patient context your workflow assembled three or four steps earlier, across a form submission, an EHR lookup, and an eligibility check. Privent runs inside that workflow, at the point where the context is built, not after it has already left.
The goal is not to stop AI from helping with patient care. It is to keep patient data under control while it does.
Privent Session
Place this immediately after your trigger. It opens a session and generates a session ID and a trace ID. Every downstream Privent node reads from that same session, so a single execution stays traceable end to end.
Privent Tokenize
Point it at the field headed for the model. It scans for PHI and secrets, including email addresses, phone numbers, Social Security numbers, card numbers, and more, and replaces each detection with a deterministic placeholder. An address like alice@acme.com becomes [EMAIL_001], and the model only ever sees the token.
Privent Risk Check
Scores the tokenized payload across four tiers, Low, Medium, High, or Critical. Use it as a Switch source to route High or Critical requests to a human reviewer or a private model, without blocking the rest of the workflow by default.
Model call
Your n8n workflow sends the tokenized text to whatever model you have chosen, external, private, or a clinical summarization service. None of it ever contains a real patient identifier.
Privent Detokenize
Placed immediately before a trusted egress point, an EHR update or an internal case-management API. In strict mode it checks the destination against your trusted-sink list, and anything that is not on that list keeps the token instead of the original value.
Privent Handoff and Audit
Handoff logs every delegation between agents or out to an external sink. Audit captures the rest, risk score, data category, policy decision, and timestamp, all without storing the raw prompt. That gives your compliance team a structured trail to review instead of a folder of transcripts.
A consistent token lets a model follow the shape of a patient case, this looks like an email, this looks like a date, without ever seeing the plaintext behind it. At an approved destination, Privent restores the original value for the system that is actually authorized to see it.
Privent sits where your n8n workflow collects and composes data, so your team can govern what leaves the workflow before it reaches an external service, not after the fact.
Run Privent Cloud for a fast start, a dedicated environment for isolation, or deploy fully on-prem, detection stack and AI models included, when the environment requires it to stay inside your network.
Privent is a technical control, not a compliance certificate. Here is how it maps to the questions security and compliance teams tend to ask first.
We will map one live workflow with your team, point out where PHI is exposed today, and show exactly where Privent's six operations fit, without redesigning your orchestration.
No production patient data is needed for the first conversation.
Privent is a technical control that supports your organization's HIPAA security and compliance program. It does not, on its own, make a workflow, a customer, or a deployment HIPAA compliant. Your organization remains responsible for determining the legal, regulatory, and contractual requirements that apply to its use of AI and patient data.
