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Description
Keep personal and confidential data out of AI prompts. Guardrails is a privacy-first AI assistant for nonprofits and mission-driven teams. It helps you use tools like ChatGPT, Claude, and Google Gemini safely, without exposing sensitive information. Why Guardrails? Teams are increasingly using AI to draft emails, analyse reports, and summarise casework. But copying real data into AI tools can expose personal, donor, or beneficiary information. Guardrails solves this by acting as a protective layer between you and AI tools, directly in your browser. What it does 1. Detects sensitive data instantly Scans what you type or paste into AI tools and identifies personal or high-risk information. 2. Automatically redacts or anonymises Masks names, emails, case details, and other sensitive data before it is sent. 3. Explains what and why Shows exactly what was changed and gives clear, simple explanations so you understand the risks. 4. Teaches safe AI use as you work Provides short tips and micro-lessons on topics like GDPR, privacy, and responsible AI. 5. Works with your existing tools Use your preferred AI platforms and API keys while applying consistent protection rules. Key features Real-time PII detection and redaction Multiple modes: mask, pseudonymise, or block Transparent “before and after” view of prompts Lightweight and fast, no complex setup Built-in learning prompts and guidance Designed for nonprofits, NGOs, and ethical teams Who it’s for Nonprofits and charities Social enterprises and cooperatives Teams handling sensitive or personal data Anyone who wants to use AI more responsibly Your data stays protected Guardrails is built around privacy and dignity: Data is processed locally or securely, depending on setup No data is used to train external AI models Clear visibility into what happens to your data Our mission We believe organisations should be able to use AI without compromising the people they serve. Guardrails helps teams adopt AI with confidence, while protecting privacy and building real understanding.