Launching today

Privaro

Launching today

Runtime PII detection and governance proxy for LLMs

5 followers

Runtime PII detection and governance proxy for LLMs

5 followers

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Privaro sits between your application and any AI model, intercepting every prompt before it reaches the model. It detects and tokenizes sensitive data — names, emails, IBANs, national IDs, medical records, contract clauses — in under 80ms. The model works on tokens, not real data. And every interaction generates a blockchain-certified audit trail. Built for teams shipping LLM features in regulated industries (fintech, legal, healthcare, insurance) who need to prove GDPR and EU AI Act compliance.

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Launch tags:Privacy•Developer Tools•Artificial Intelligence

Launch Team / Built With

ReplayAutonomous app testing for teams who ship at AI-speed

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OpenAI

GPT-6 Astra Challenge

What real task does your product handle with GPT-6 Astra?

Maker

Privaro acts as the governance layer for GPT-6 Astra deployments in regulated enterprises. When a legal firm, fintech, or healthcare provider connects their application to GPT-6 Astra, Privaro intercepts every prompt before it reaches the model — detecting and tokenizing sensitive data (client names, IBANs, medical records, contract clauses) in under 80ms — and generates a blockchain-certified audit trail for every interaction. The real task: enabling enterprises to use GPT-6 Astra with real customer data, without exposing that data to the model or losing the ability to prove what the AI processed. A legal AI assistant using GPT-6 Astra can analyze contracts containing client PII — Privaro ensures the model only sees tokenized versions, the lawyer receives the response with real values restored, and the firm has a certified record of every AI interaction for GDPR and EU AI Act compliance. Privaro makes GPT-6 Astra enterprise-ready in regulated sectors where data governance

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23h ago

Maker

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Hi Product Hunt! 👋 I'm Miguel Ángel, founder of Privaro. The problem we solve: every time your app sends a prompt to GPT-4 or Claude, it leaks whatever your users typed — names, emails, financial data, health records. That data leaves your infrastructure. You have no record of what was sent. And if a regulator or enterprise customer asks "what did your AI see?" — you can't answer. Privaro is the layer that sits between your app and the LLM. It detects and tokenizes sensitive data before the model sees it, and generates a certified audit log for every interaction. We built this after seeing the same pattern repeat: companies with great AI products losing enterprise deals because they couldn't answer the compliance question architecturally. The free trial is live — 500 requests, no credit card. Would love your feedback, especially from anyone building in fintech, legal or healthcare. Those are the verticals where this pain is most acute. What would you want to see in a tool like this?

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3d ago

Maker

Hi, I'm Miguel Ángel, co-founder of Privaro. Wanted to add some context here as the maker, not as a user review.
We built Privaro after seeing the same gap repeatedly in regulated industries (banking, insurance, legal, healthcare): companies are using GPT-4, Azure OpenAI, or Claude in production, but can't answer a basic question their DPO or an auditor will ask — "what personal data has actually gone through this model in the last 12 months?"
Privaro sits as a proxy layer between your code and the LLM API: it tokenizes PII in real time before it reaches OpenAI, Azure, Anthropic, or Gemini, transparently detokenizes the response, and generates an auditable log ready for compliance review (GDPR, AI Act).
We're currently live in production with an enterprise client (Octupus Technologies / Robin AI platform) and going through public R&D funding processes (CDTI, CAM) in Spain to accelerate the compliance-focused roadmap.
Happy to answer technical questions here about the tokenization approach or multi-LLM architecture. Feel free to also check us out at privaro.ai.

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20h ago

Forum Threads

p/privaro

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2d ago

AI governance, compliance and security — the practical guide

Field notes from shipping governance infrastructure for legal, fintech and healthcare teams. No fluff, no vendor speak.

https://privaro.ai/blog

p/privaro

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2d ago

Privaro integration

Detect and tokenise PII before it reaches any LLM. One endpoint change no architecture rewrite.

https://privaro.ai/docs

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Hi, I'm Miguel Ángel, co-founder of Privaro. Wanted to add some context here as the maker, not as a user review.
We built Privaro after seeing the same gap repeatedly in regulated industries (banking, insurance, legal, healthcare): companies are using GPT-4, Azure OpenAI, or Claude in production, but can't answer a basic question their DPO or an auditor will ask — "what personal data has actually gone through this model in the last 12 months?"
Privaro sits as a proxy layer between your code and the LLM API: it tokenizes PII in real time before it reaches OpenAI, Azure, Anthropic, or Gemini, transparently detokenizes the response, and generates an auditable log ready for compliance review (GDPR, AI Act).
We're currently live in production with an enterprise client (Octupus Technologies / Robin AI platform) and going through public R&D funding processes (CDTI, CAM) in Spain to accelerate the compliance-focused roadmap.
Happy to answer technical questions here about the tokenization approach or multi-LLM architecture. Feel free to also check us out at privaro.ai.