I'm the creator of the PII Firewall Edge API (currently on RapidAPI).
I saw a lot of devs struggling to implement safety guardrails correctly—most were just using basic regex or heavy LLMs that hallucinate.
So, I decided to package my API into a full-featured UI/Toolkit called Risk Mirror.
What it does: It sits between your users and your LLM (OpenAI/Anthropic) and strips out sensitive data before it leaves your server.
The Tech (Zero AI Inference): Instead of asking an LLM "is this safe?", I use:
152 PII Types: My custom engine covers everything from US Social Security Numbers to Indian Aadhaar cards and HIPAA identifiers.
Shannon Entropy: To detect high-entropy strings (API keys, passwords) that regex misses.
Deterministic Rules: 100% consistency. No "maybe."
Why use this?
It's Tested: The underlying API engine is already battle-tested.
It's Fast: <10ms latency.
Includes a 'Twin Dataset' generator for Data Scientists (redact CSVs securely). Feedback welcome!"
Raviteja_•34m ago
I'm the creator of the PII Firewall Edge API (currently on RapidAPI).
I saw a lot of devs struggling to implement safety guardrails correctly—most were just using basic regex or heavy LLMs that hallucinate.
So, I decided to package my API into a full-featured UI/Toolkit called Risk Mirror.
What it does: It sits between your users and your LLM (OpenAI/Anthropic) and strips out sensitive data before it leaves your server.
The Tech (Zero AI Inference): Instead of asking an LLM "is this safe?", I use:
152 PII Types: My custom engine covers everything from US Social Security Numbers to Indian Aadhaar cards and HIPAA identifiers. Shannon Entropy: To detect high-entropy strings (API keys, passwords) that regex misses. Deterministic Rules: 100% consistency. No "maybe." Why use this?
It's Tested: The underlying API engine is already battle-tested. It's Fast: <10ms latency.
Includes a 'Twin Dataset' generator for Data Scientists (redact CSVs securely). Feedback welcome!"