This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
AI agents send raw data to LLMs on every run: emails, records, API keys, secrets. n8n's own Guardrails node can redact that, but redaction is permanent, the data never comes back. Privent tokenizes PII and secrets before they reach the LLM, then reverses it safely at a trusted sink. Official n8n Integration Partner, live today. Local mode runs fully offline. Built for teams running agent workflows in production who cannot afford a single leaked record.
Hey Product Hunt! Some of you might remember our first launch here as an AI monitoring
Chrome extension. Since then we pivoted: instead of watching what leaves the browser, we
went inside the workflow engine itself, where agents actually send data to the LLM.
Privent now tokenizes PII and secrets before they reach the model, then reverses it safely
once you are back in a trusted system. n8n's own Guardrails node can redact that data, but
redaction is permanent, ours comes back. It is live today as an official verified n8n node.
Local mode runs fully offline if you never want data leaving your infrastructure.
Curious to know: where has your team been most nervous about what your agents are actually
sending to the LLM?
the reversible-tokenization vs permanent-redaction distinction is the actual pitch here, but it made me wonder about a specific failure mode - if the LLM doesn't just echo the token back verbatim but paraphrases around it in its response (rewrites the sentence, changes word order, summarizes multiple tokenized fields into one line), can the reversal still find and swap back the original values, or does detokenization depend on the token surviving untouched in the output?
Quick tool for the PH community!
Before setting up Privent, if you want to test whether your current n8n workflows are actually exposing sensitive data, we built a free n8n Risk Scanner.
Short sweet and solves a very real problem. Congrats for shipping 🙌 one question how does Privent handle structured JSON payloads where secrets or PII are nested deep inside dynamic key-value pairs?
About Privent 2.0 on Product Hunt
“Runtime Data Control for n8n Workflows”
Privent 2.0 was submitted on Product Hunt and earned 29 upvotes and 10 comments, placing #20 on the daily leaderboard. AI agents send raw data to LLMs on every run: emails, records, API keys, secrets. n8n's own Guardrails node can redact that, but redaction is permanent, the data never comes back. Privent tokenizes PII and secrets before they reach the LLM, then reverses it safely at a trusted sink. Official n8n Integration Partner, live today. Local mode runs fully offline. Built for teams running agent workflows in production who cannot afford a single leaked record.
Privent 2.0 was featured in Developer Tools (516.4k followers), Artificial Intelligence (474.4k followers) and Security (2.8k followers) on Product Hunt. Together, these topics include over 191.7k products, making this a competitive space to launch in.
Who hunted Privent 2.0?
Privent 2.0 was hunted by Asil Ozyildirim. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Privent 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Asil Ozyildirim