How to Build a Chat with Knowledge Base AI Agent
An AI agent that lets employees ask questions and get accurate answers sourced directly from internal docs.
Connectors and tools
Google Drive
Notion
Google Docs
Created by
xpander.ai
Built for
Enterprise developers and AI engineers
Operations and IT managers
Customer support and success teams
Compliance and legal departments
Useful links
Challenge
This agent resolves the operational bottleneck caused by fragmented institutional knowledge, where critical information is siloed across disparate tools and wikis. It eliminates the inefficiency of traditional keyword search by providing precise, synthesized answers grounded in a single source of truth. This reduces the time wasted on manual discovery and minimizes the dependency on subject matter experts for routine inquiries, streamlining enterprise operations and workflow automation.
How the AI agent works
Below is how the AI agent works:
1. User input query: The agent lets users insert their queries in natural language.
2. Knowledge retrieval: The agent retrieves the knowledge, based on the tools connected, and ground the response to it.
3. Agent response: An LLM analyses the query and responds based on the knowledge it has learned in the provided knowledge base.
Key benefits
- Accelerated production deployment: Rapidly build and deploy knowledge-grounded agents using a pre-configured template, reducing time-to-market for enterprise AI initiatives.
- Enhanced workflow automation: Streamline internal support and information retrieval processes by integrating autonomous agents that provide instant, accurate answers.
- Scalable knowledge management: Efficiently manage growing volumes of documentation and data without degrading search quality or response accuracy.
- Enterprise-grade reliability: Ensure consistent, policy-compliant responses with grounded RAG architecture, a best practice for agents in production.
