mpakaobed

exactly i am actually working on complicated it can be if the model has to reason around the data, we use a combination of regex patterns, named entity recognition, and context aware detection to identify and tag PHI, PCI, and PII before tokenization. AWS doesn't do this for us that's actually the gap we built around.

Our approach is that tokens are format preserving and semantically typed. The model knows it's handling a name, a dollar amount, a diagnosis code it just never sees the real value.

Hey , i built this SDK + 16 thousands lines of code on this idea of making AI agents that never see your data. we have been #12 on product hunt yesterday. all that sounds good but i need real hard truth feedback about the tool , it's free , use the api and ask for more on the comment if needed but i need hard truth feedback on this project, it did work with us but need y'all to tell me. does it work ? is it slow ? like all kinds of feedback , thank you !

Four months ago, someone at AWS asked me how Bedrock prevents LLMs from seeing customer data.Casual office conversation. Nothing serious. But it turned into a real discussion AWS's entire business is built on data protection, and here were all these giants calling AI agents the next big thing. Agents that, by default, see everything.I said AWS hasn't built that layer yet. But they will.That gap became astra.

Your agent gets tokens instead of real data. It reasons, decides, acts real values only resolve at execution. PHI, PCI, PII never touch the model context. Two lines of code, works with whatever you're already running.codeastra.dev That's what i am working on , did some test but need more customers review on that.