Knight Agent
This agent is an intelligent corporate AI assistant powered by agentic RAG architecture: autonomous knowledge management, multi-step reasoning capabilities, and analytics dashboards that empower HR teams while dramatically reducing helpdesk volume.
About this project
Knight Agent is an advanced corporate AI assistant built on FastAPI and React, designed to optimize internal employee support through intelligent document-based responses. Unlike conventional chatbots, the system employs an agentic RAG (Retrieval-Augmented Generation) architecture powered by LangGraph, enabling multi-step reasoning, dynamic query refinement, and self-reflection capabilities that ensure high-quality, contextually accurate responses grounded in corporate documentation.
The platform's knowledge management interface empowers HR managers and administrators with complete control over the AI's knowledge base. Through an intuitive document management system, they can upload new policies, remove outdated materials, and curate useful links and downloadable forms, all without technical expertise. The system automatically handles document processing, chunking, and vectorization using BGE-m3 multilingual embeddings optimized for Portuguese, transforming raw documents into searchable knowledge within minutes.
By providing employees with instant, document-backed answers to their questions, Knight Agent significantly reduces helpdesk ticket volume and response times. Whether employees need information about benefits, company policies, vacation procedures, or operational guidelines, the AI retrieves relevant context from the corporate knowledge base and generates accurate, helpful responses. The hybrid search system combines semantic understanding with keyword matching, ensuring comprehensive retrieval even for complex queries.
The analytics layer delivers actionable insights through real-time dashboards that track conversation volumes, document utilization, response times, and user engagement patterns. Managers can monitor which documents are most frequently accessed, identify knowledge gaps in the documentation, and measure the system's impact on support operations. These metrics enable continuous optimization of the knowledge base and demonstrate clear ROI through reduced support costs and improved employee satisfaction.