I’ve been building Guardrail Layer, an open-source, self-hosted backend that acts as a data privacy firewall between your database and any AI model, dashboard, or automation tool.
It automatically enforces redactions, access control, and audit logging, so you can safely connect LLMs or analytics systems to real data without leaking sensitive information.
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Recent update
Just released Global Regex Redactions — pattern-based rules (like emails, SSNs, or credit cards) that apply across all tables automatically.
Other improvements:
• Expanded audit logging (create, update, delete events)
• Cleaner, more modern redaction management UI
• Docker setup reliability
• Foundation for role-based access control
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How it works
• Runs locally or via Docker Compose
• Connects to PostgreSQL or MySQL
• Provides a web UI for managing connections, regex rules, and audit logs
• Works with AI query interfaces (e.g. natural language → SQL)
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Example use cases
• Safely connect a local or hosted LLM to your production database
• Build internal chatbots or dashboards without exposing PII
• Enforce consistent privacy rules across teams or tools
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It’s early-stage but functional, and I’d love feedback on what privacy or compliance features you’d want next.
Repo: https://github.com/tyoung1996/guardrail-layer
Comments URL: https://news.ycombinator.com/item?id=45827921
Points: 1
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Source: news.ycombinator.com
