A Dialog-Based Multi-Agent System for Context-Aware Financial Analysis in SMEs

This paper presents a dialog-based AI financial assistant designed to support small and medium-sized enterprises (SMEs) in interpreting their financial indicators. The system combines a modular multi-agent architecture with context engineering techniques (explicit agent roles, controlled function calls, and structured hand-offs) to analyze and explain financial data in natural language. A prototypical cash-flow analysis, embedded within a production platform, demonstrates how the assistant enables interactive communication of financial information, thereby improving access to managerial and financial knowledge for non-experts.