Layer8 Secure Middleware
Layer8: A privacy shield for AI interactions. It anonymizes sensitive data before reaching AI and safeguards your private information. What VPNs did for internet privacy, Layer8 now does for AI.
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Descripción
Layer8 is a security framework that keeps your sensitive information private when interacting with AI systems like ChatGPT, Gemini or Claude. It works by automatically replacing private details (like names, emails, and company data) with anonymous placeholders before sending your text to any AI service, then converts the AI's response back to include your original information.
Our solution offers multiple ways to protect your data:
A browser extension that encrypts your data locally
A self-hosted Docker option to run AI models on your own hardware
Cloud services with hardware-level security protections
API services for developers
Whether you're concerned about sharing company secrets, personal information, or confidential data, Layer8 creates a protective barrier between you and AI systems. It's perfect for professionals who need AI assistance but can't risk exposing sensitive information.
Simple to set up and use, Layer8 gives you the benefits of AI without the privacy concerns.
Progreso del hackathon
Hour 0-1: Planning & Setup Team formation and project overview Environment setup and repository initialization Task distribution and timeline review Hours 2-4: Core Anonymizer Development Implement basic NER-based anonymization Build pattern matching for sensitive data Create token generation and tracking system Hours 5-7: Deanonymization & API Framework Develop deanonymization logic Set up REST API structure Create basic request/response handling Hours 8-10: LLM Integration Connect to LLM providers (OpenAI, Claude, Gemini) Implement query processing pipeline Test end-to-end flow Hours 11-13: Chrome Extension Develop extension structure Implement request interception Add client-side encryption/decryption Hours 14-16: Docker Solution Configure Docker container Integrate local LLM setup Test containerized solution Hours 17-19: Testing & Refinement End-to-end testing Bug fixes and performance optimization Security audit Hours 20-22: Documentation & UI Polish Complete README documentation Refine user interfaces Create setup guides Hours 23-24: Final Preparations Prepare demonstration Create project presentation Final debugging and polishing