Case Study - Private AI Document Query
Financial professionals trust LLG for secure AI deployment. Our open-source models prevent data leakage.
Case Study: Private AI Document Query by LLG
Challenge: Customers who want to use LLMs but cannot risk leaking any data. They need a secure way to query their private documents without compromising privacy.
Solution: Large Language Games (LLG) developed 'Confidant.' This is a single-tenant AI model, basically an AI model deployed and maintained just for you. No data ever leaves your AI environment. This allows LLG to provide a private app enabling AI and LLM users to query their private documents, such as notes, PDFs, and Excel files, without compromising privacy. The information remains completely private and never touches any foundational models like OpenAI or Anthropic.
Features:
- Systematized Inquiry: Users can query private documents seamlessly through chat.
- Complete Privacy: Ensures that all data remains private and secure, with no interaction with external AI models.
- AI-Powered Insights: Provides the latest AI capabilities, controlled entirely by the user.
Results: By integrating Confidant, customers achieve a secure and efficient way to query their private documents, benefiting from the latest AI advancements without risking data leaks.