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
A high-performance, privacy-first PII detection and anonymization toolkit written in Rust.
Key Features:
- β‘ Deterministic Rust engine with zero-copy analysers and calibrated confidence scoring
- π 48+ validation-backed recognizers with confidence evidence trails (SSN, Credit Card, IBAN, Passports, Phone Numbers, Emails, and more)
- π§° Unified API surface for Rust, Python, Node.js, and WebAssembly
- π οΈ Batteries-included CLI for quick redaction and bulk jobs
- π Perfect precision for high-confidence detections (β₯0.85 achieve P=1.000 for checksum-based recognizers)
- π 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
π Spec Kitty
A specification-first development framework with live kanban dashboard and AI agent orchestration, built on GitHub's Spec Kit.
Key Features:
- π Live Kanban Dashboard β Real-time visibility into work across planned β doing β for review β done lanes
- π Multi-Agent Orchestration β Coordinate multiple AI coding agents (Claude Code, GitHub Copilot, Gemini CLI, Cursor, Windsurf, and more)
- π― Spec-Driven Development β Flip the traditional model: specifications become executable, directly generating working implementations
- π¦ Artifact Management β Track specifications, plans, tasks, and deliverables in one integrated workspace
- π§ Agent-Aware Prompts β Scaffolding commands tuned to each AI agent's capabilities
- β‘ Zero Configuration β Automated dashboard starts with
spec-kitty init - π³ Worktree Strategy β 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:
- Constitution β Establish project principles and governance
- Specify β Define requirements and user stories
- Clarify β Structured discovery interviews to reduce ambiguity
- Plan β Create technical implementation plans with your tech stack
- Tasks β Break down into actionable work packages
- Implement β Execute with AI agent assistance
- Review β Validate and move to done
- Accept & Merge β 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 claudeRepository: github.com/Priivacy-ai/spec-kit
We believe that building compliant, privacy-first software shouldn't be painful. Our projects solve two critical problems:
-
Priivacy Rust β Detect and redact sensitive data with confidence, speed, and accuracy. Stop shipping PII in logs, databases, and exports.
-
Spec Kitty β 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.
- Read the Spec Kitty README
- Run
spec-kitty --helpfor CLI reference - Check playbook examples:
- Multi-agent feature development
- Parallel implementation tracking
- Dashboard-driven development
- Claude + Cursor collaboration
Spec Kitty is released under the MIT License.
- Report Issues: Spec Kitty Issues
- Website: priivacy.ai
- Discussions: Check GitHub Discussions in each repository
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 β€οΈ by the Priivacy AI team