Background
Many users are most concerned about data privacy when utilizing AI technology, especially when it comes to commercially sensitive data or personal privacy information. Traditional cloud-based AI services carry the risk of data leakage and require reliable localized solutions.
Core Solutions
- Local Run Architecture with Lemon AI: The framework runs entirely locally and data processing is not transferred to the cloud. All computational tasks are performed through local large language models (e.g. DeepSeek/Qwen) supported by Ollama.
- Configure the virtual machine sandbox environment: Lemon AI provides a sandbox-isolated execution environment that prevents data leakage, and all code runs are done inside the container without affecting or accessing the host system.
- Implementation of closed-loop management of local data: The entire process from data input, processing to output is done on a user-controlled device, and it is recommended that Lemon AI be deployed on an on-premises server or personal workstation.
operation suggestion
1. Ensure that all cloud connectivity options are disabled during installation
2. Regularly check network traffic to confirm that there is no outgoing data
3. For highly sensitive data, consider physically isolating the deployment environment
This answer comes from the articleLemon AI: A Locally Running Open Source AI Intelligence Body FrameworkThe
May not be reproduced without permission:AI productivity tools " How to address data privacy concerns when running AI intelligences locally?
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