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).
Pryvra is an open-source privacy runtime for AI applications. It tokenizes sensitive customer data before it reaches an LLM, keeps the encrypted mapping in your environment, and restores it only at trusted boundaries.
AI agents are becoming the front door for customer conversations. But when a customer shares an email, phone number, account number, PAN, Aadhaar, or card detail, that data can end up directly inside an LLM prompt.
I built Pryvra to change that.
Pryvra replaces sensitive values with stable tokens before the model call. The model receives useful context without receiving the underlying customer data. The encrypted mapping stays in your environment and can be restored only where it is trusted, such as a human-agent handoff.
What Pryvra supports today:
• Detection for emails, phones, PAN, Aadhaar, IFSC, bank accounts, payment cards, and common API keys• Encrypted PII-to-token mappings• Conversation-aware stable tokens, preserving context without exposing identity• Controlled rehydration for trusted systems and human agents• Custom detectors for company-specific identifiers• Integrations for LiveKit and Pipecat• An open-source TypeScript SDK, available on npm
Pryvra is useful for voice agents, chatbots, copilots, support workflows, healthcare, fintech, SaaS, and any AI product that handles customer data.
I’d genuinely love feedback from builders: which framework, data type, or integration should we support next?
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About Pryvra on Product Hunt
“Keep customer PII out of AI prompts”
Pryvra was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #88 on the daily leaderboard. Pryvra is an open-source privacy runtime for AI applications. It tokenizes sensitive customer data before it reaches an LLM, keeps the encrypted mapping in your environment, and restores it only at trusted boundaries.
Pryvra was featured in Open Source (68.7k followers), Developer Tools (517.4k followers), Artificial Intelligence (475.9k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 233.7k products, making this a competitive space to launch in.
Who hunted Pryvra?
Pryvra was hunted by Sahil Rajput. 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 Pryvra stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sahil Rajput
AI agents are becoming the front door for customer conversations. But when a customer shares an email, phone number, account number, PAN, Aadhaar, or card detail, that data can end up directly inside an LLM prompt.
I built Pryvra to change that.
Pryvra replaces sensitive values with stable tokens before the model call. The model receives useful context without receiving the underlying customer data. The encrypted mapping stays in your environment and can be restored only where it is trusted, such as a human-agent handoff.
What Pryvra supports today:
• Detection for emails, phones, PAN, Aadhaar, IFSC, bank accounts, payment cards, and common API keys• Encrypted PII-to-token mappings• Conversation-aware stable tokens, preserving context without exposing identity• Controlled rehydration for trusted systems and human agents• Custom detectors for company-specific identifiers• Integrations for LiveKit and Pipecat• An open-source TypeScript SDK, available on npm
Pryvra is useful for voice agents, chatbots, copilots, support workflows, healthcare, fintech, SaaS, and any AI product that handles customer data.
I’d genuinely love feedback from builders: which framework, data type, or integration should we support next?
GitHub: https://github.com/sahil-rajput/pryvra