Enterprise PII Guardrails Studio

Enterprise PII Guardrail Studio is a high-performance, enterprise-grade AI safeguard gateway designed to detect, mask, redact, and pseudonymize Personally Identifiable Information (PII) before it reaches Large Language Models (LLMs) or third-party APIs.

Key Features

• Blazing Fast Masking: Sub-25ms sustained masking latency with in-memory caching and background async audit logging.
• Enterprise-Grade Privacy: Detects 30+ sensitive entities including SSN, Credit Cards, IBAN, Passports, API keys, Names, Addresses, Medical IDs, and more.
• Encrypted Storage: Local audit logs and security telemetry secured with SQLCipher AES-256 encrypted database.
• Hardware-Locked Licensing: Anti-tampering, node-locked hardware integrity verification.
• Zero-Footprint Cleanup: Automatic orphaned temp purging prevents %TEMP% disk bloat across repeated runs.
• Modern Management UI: Material Design 3 / MUI dashboard for live telemetry, access keys, policy rules, and audit logs.

Quickstart

Installation

pip install piiguardrails

Launching the Studio

piiguardrails

On first run, the core engine will automatically initialize and launch the local API server and management dashboard at:

http://127.0.0.1:8000

API Usage Example

Once the studio is running, integrate it directly into your Python LLM pipeline:

import requests

API_KEY = "your-api-key-here"  # Generated via Studio UI
headers = {"X-API-Key": API_KEY, "Content-Type": "application/json"}

payload = {
    "text": "Hello John Doe, your verification code was sent to john.doe@acme.corp",
    "risk_level": "MODERATE",
    "policy": "anonymize"
}

response = requests.post("http://127.0.0.1:8000/mask", json=payload, headers=headers)
print(response.json())
# Output: {"masked_text": "Hello <PERSON_1>, your verification code was sent to <EMAIL_ADDRESS_1>", ...}

System Requirements

• OS: Windows 10 / 11 / Windows Server (64-bit)
• Python: >= 3.8

License

Proprietary / Enterprise Commercial License. All rights reserved.