---
title: "paig"
type: "tool"
slug: "privacera-paig"
canonical_url: "https://www.graphcanon.com/tools/privacera-paig"
github_url: "https://github.com/privacera/paig"
homepage_url: "https://paig.ai"
stars: 213
forks: 220
primary_language: "CSS"
license: "Apache-2.0"
archived: false
categories: ["evaluation-observability"]
tags: ["compliance", "css", "genai", "guardrails", "security"]
updated_at: "2026-07-15T10:42:48.971797+00:00"
---

# paig

> PAIG (Pronounced similar to paige or payj) is an open-source project designed to protect Generative AI (GenAI) applications by ensuring security, safety, and observability.

PAIG (Pronounced similar to paige or payj) is an open-source project designed to protect Generative AI (GenAI) applications by ensuring security, safety, and observability.

## Facts

- Repository: https://github.com/privacera/paig
- Homepage: https://paig.ai
- Stars: 213 · Forks: 220 · Open issues: 57 · Watchers: 8
- Primary language: CSS
- License: Apache-2.0
- Last pushed: 2025-08-05T15:00:08+00:00

## Trust & health

_Signals computed from public GitHub metadata. Not a security guarantee._

- Maintenance: Slowing (computed 2026-07-15T10:42:47.249Z)
- Security scan: No lockfile (0 critical, 0 high, 0 medium, 0 low) · last scan 2026-07-15T10:42:47.578Z
- Full report: [trust report](/tools/privacera-paig/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/privacera-paig/trust)

## Categories

- [Evaluation & Observability](/categories/evaluation-observability.md)

## Tags

compliance, css, genai, guardrails, security

## Category neighbours (exploratory)

_Same-category tools for discovery only - not curated alternatives. Cap shown at six._

- [generative-ai-for-beginners](/tools/microsoft-generative-ai-for-beginners.md) - 21 Lessons for Getting Started with Generative AI (★ 112,866) [Very active]
- [llm-course](/tools/mlabonne-llm-course.md) - Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. (★ 80,904) [Slowing]
- [netdata](/tools/netdata-netdata.md) - The fastest path to AI-powered full stack observability, even for lean teams. (★ 79,594) [Very active]
- [scikit-learn](/tools/scikit-learn-scikit-learn.md) - scikit-learn: machine learning in Python (★ 66,693) [Very active]
- [TrendRadar](/tools/sansan0-trendradar.md) - AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts. (★ 60,461) [Very active]
- [headroom](/tools/headroomlabs-ai-headroom.md) - Compress tool outputs and data to reduce tokens before reaching the LLM. (★ 58,486) [Very active]

_+ 2 more not listed._

## README (excerpt)

_Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._

```text
## Quick Start

To quickly try out PAIG, you can use the Google Colab Notebook or the downloadable Jupyter Notebook. Here is the
link to the <a href="https://docs.paig.ai/index.html" target="_blank">Quick Start Guide & Documentation</a>

---

## License

PAIG is licensed under the Apache License v2. For more details, please see the [LICENSE](LICENSE) file.
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/privacera-paig`](/api/graphcanon/tools/privacera-paig)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_