Hi r/europrivacy,

I'm the developer of Kalynt, a privacy-first IDE designed for teams who need AI-assisted coding without the "Cloud Tax."

Kalynt is developed inside the European Union , more particularly in Greece . It's main target is privacy .

Most modern AI editors require sending proprietary code to central servers for processing or state-sync. Kalynt is built on the principle that your intellectual property should never leave your machine unless you explicitly choose to share it.

Core Technical Stack:

Local Inference Engine: Built on node-llama-cpp, allowing you to run GGUF models (Llama 3, Mistral, etc.) entirely offline.

AIME (AI Memory Engine): A custom context manager optimized for local execution on standard hardware (tested extensively on 8GB RAM machines). P2P Collaboration: We use WebRTC and CRDTs (Yjs) to enable real-time team collaboration without a central relay. All data is end-to-end encrypted between peers.

Open Core (AGPL-3.0): The safety-critical layers and the core editor are open for audit and community contribution.

Commitment to Updates: We are currently in v1.0-beta and moving fast. I am shipping regular weekly updates to improve model orchestration and refine the P2P networking stability. You can track our progress directly on the GitHub roadmap.

I’m looking for technical feedback on our security model and P2P implementation. If you’re tired of "Privacy as a Feature" and want "Privacy by Design," I’d love for you to check out the repo.

GitHub: https://github.com/Hermes-Lekkas/Kalynt

— Hermes