Ground Retrieval Augmented Generation(RAG) workflows in Large Language Model (LLM) in the organizations’ owned data, vector databases or knowledge graphs without exposing chat prompts, responses and history.
Inputs and Outputs
GenAI outputs may be unreliable, containing biased or copyrighted material, risking confidentiality and legality. Hosting AI on SafeLIShare mitigates risks, ensuring data integrity and confidentiality.
Privacy and Data Protection
Utilizing private data in AI models risks leakage and regulatory violations. SafeLIShare provides robust solutions, upholding privacy standards and empowering organizations to control sensitive information
Cybersecurity
AI integration introduces security threats like injection attacks and unauthorized access. SafeLIShare enhances cybersecurity posture, safeguarding against emerging AI-related threats.
Access Control
Gain granular control over access to private data, ensuring only authorized individuals can view and interact with sensitive information.
Logging
Access auditable data plane logs (who accessed what data) and control plane logs (who changed settings or policy), ensuring transparency and accountability in data handling through confidential computing.
Data Repository
Access a list of all your protected data, along with descriptive tags for each dataset, to simplify data management and compliance tasks.
Encryption Key Exchange
Secure your conversation AI experience with encrypted secure enclaves, preventing direct access to private data and offering strong defense against unauthorized intrusion.
Promises of Privacy
Prompts are end-to-end protected. We cannot see your queries, responses, chat history, or any login information, guaranteeing your privacy.
Experience the power of
SafeLIShare ConfidentialRAG® to safeguard your
data and ensure confidentiality in AI applications.