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Priivacy AI

Welcome to Priivacy AI! We're building the next generation of privacy-first tools for compliance, security, and software development.

Visit our website: priivacy.ai


Our Projects

🔐 Priivacy

A high-performance, privacy-first PII detection and anonymization toolkit written in Rust.

Key Features:

  • Deterministic Rust engine with zero-copy analysers and calibrated confidence scoring
  • 🔐 48+ validation-backed recognizers with confidence evidence trails (SSN, Credit Card, IBAN, Passports, Phone Numbers, Emails, and more)
  • 🧰 Unified API surface for Rust, Python, Node.js, and WebAssembly
  • 🛠️ Batteries-included CLI for quick redaction and bulk jobs
  • 📊 Perfect precision for high-confidence detections (≥0.85 achieve P=1.000 for checksum-based recognizers)
  • 🌍 Multi-language support with POS-enhanced recognition (English, German, Spanish, French) plus 70+ additional languages

What it does: Priivacy reimagines Microsoft's original privacy toolkit with a modern, low-latency core. It detects and redacts personally identifiable information (PII) with deterministic confidence scoring, validation-backed accuracy, and first-class support for multiple programming languages and WebAssembly.

Supported PII Types:

  • National IDs (US SSN, UK NHS, AU TFN, Poland PESEL, Brazil CPF, China ID, India Aadhaar, +20 more)
  • Financial data (Credit Cards with Luhn validation, IBAN, ABA Routing, Bank Accounts, Crypto Addresses)
  • Documents (Passports, Driver Licenses, Medical Licenses)
  • Structured data (Phone Numbers, URLs, Email, IP Addresses, Dates, Times)

Latest Version: v0.3.0

  • Deterministic Confidence Scoring with 0.0-1.0 calibrated scores
  • 35+ checksum-validated recognizers for accuracy
  • F1 improvements ranging from 5-15% across all recognizer tiers
  • Zero-copy performance with <2x processing overhead

A specification-first development framework with live kanban dashboard and AI agent orchestration, built on GitHub's Spec Kit.

Key Features:

  • 📊 Live Kanban Dashboard – Real-time visibility into work across planned → doing → for review → done lanes
  • 🔄 Multi-Agent Orchestration – Coordinate multiple AI coding agents (Claude Code, GitHub Copilot, Gemini CLI, Cursor, Windsurf, and more)
  • 🎯 Spec-Driven Development – Flip the traditional model: specifications become executable, directly generating working implementations
  • 📦 Artifact Management – Track specifications, plans, tasks, and deliverables in one integrated workspace
  • 🔧 Agent-Aware Prompts – Scaffolding commands tuned to each AI agent's capabilities
  • Zero Configuration – Automated dashboard starts with spec-kitty init
  • 🌳 Worktree Strategy – Isolated sandboxes for parallel feature development

What it does: Spec Kitty changes how teams build software by emphasizing specification-first rigor. Instead of treating specs as throwaway documents, they become the source of truth that drives implementation. The built-in dashboard gives you real-time insights into your AI-assisted development workflows, showing exactly which agents are working on what and how tasks move through your kanban board.

Workflow:

  1. Constitution – Establish project principles and governance
  2. Specify – Define requirements and user stories
  3. Clarify – Structured discovery interviews to reduce ambiguity
  4. Plan – Create technical implementation plans with your tech stack
  5. Tasks – Break down into actionable work packages
  6. Implement – Execute with AI agent assistance
  7. Review – Validate and move to done
  8. Accept & Merge – Finalize and integrate

Supported AI Agents:

  • Claude Code
  • GitHub Copilot
  • Gemini CLI
  • Cursor
  • Windsurf
  • Qwen Code
  • opencode
  • Amazon Q Developer CLI
  • Kilo Code
  • Auggie CLI
  • Roo Code
  • Codex CLI

Installation:

# From PyPI (Recommended)
pip install spec-kitty-cli

# Or with uv
uv tool install spec-kitty-cli

# Initialize a new project
spec-kitty init my-project --ai claude

Repository: github.com/Priivacy-ai/spec-kit


Why Priivacy AI?

We believe that building compliant, privacy-first software shouldn't be painful. Our projects solve two critical problems:

  1. Priivacy Rust – Detect and redact sensitive data with confidence, speed, and accuracy. Stop shipping PII in logs, databases, and exports.

  2. Spec Kitty – Build software faster by making specifications executable. Stop writing code in a vacuum; let AI agents follow a structured blueprint that guides implementation from requirements through delivery.

Together, they form a modern developer toolkit for shipping privacy-compliant features at scale.


Getting Started

For Spec Kitty (Spec-Driven Development)

  • Read the Spec Kitty README
  • Run spec-kitty --help for CLI reference
  • Check playbook examples:
    • Multi-agent feature development
    • Parallel implementation tracking
    • Dashboard-driven development
    • Claude + Cursor collaboration

License

Spec Kitty is released under the MIT License.


Community & Support


Contributing

We welcome contributions! Please open an issue or pull request in the relevant repository. Be sure to follow the project's code of conduct and contribution guidelines.


Built with ❤️ by the Priivacy AI team

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The makers of Priivacy PII detection, and Spec-Kitty

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