GoSearch uses LLMs to drive its advanced search capabilities and AI-powered features. LLMs enable GoSearch to understand user queries in natural language, deliver relevant search results, and provide AI-generated summaries. GoSearch’s implementation of LLMs is designed to maximize user value and maintain enterprise-grade security, privacy, and compliance.
How do LLMs and RAG improve GoSearch results
GoSearch uses LLMs and Retrieval-Augmented Generation (RAG) to power semantic search, chat-based assistance, AI summarization, and contextual answer generation.
When a user submits a query, the LLM interprets the meaning, intent, and context rather than just keyword matching. This enables GoSearch to surface information even when exact search terms aren’t present, dramatically improving discoverability and accuracy.
LLMs are also used in GoAI chat, custom agents, and task automation, allowing users to ask questions, summarize resources, and interact with data conversationally.
Data Security and Privacy
GoSearch’s approach to LLMs puts security and privacy first:
- Query context and results shared with the LLM are strictly limited to resources the user is permitted to view. GoSearch never sends the full database to the LLM, only narrowly scoped data relevant to each query is used.
- All communications between GoSearch and the LLM are encrypted using industry best practices. Customers can enable BYOC (bring your own cloud) options, retaining full control over data residency and compliance protocols.
- GoSearch has ZDR (zero data retention) agreements with LLM providers so that queries and data are not stored, used for training, or retained by LLM vendors.
- GoSearch supports multiple LLM providers and allows organizations to select which engine is best for their needs. Admins can switch between models and set controls to balance accuracy and speed.
You should now have a greater understanding of how GoSearch leverages LLMs. If you need further assistance, please consult the GoSearch Help Center, Contact Technical Support, or Chat with Us.
