Multi-agent systems for improved information retrieval - leveraging autonomous agents and LLM models

In the era of dynamic technological development and growing needs for data processing and analysis, the architecture of multi-agent systems is gaining importance. These systems, combined with Large Language Models (LLMs), offer an innovative approach to the information retrieval process that can enhance the efficiency, speed, and reliability of fact-finding and question-answering. This paper proposes the use of a designed multi-agent system architecture that uses autonomous agents and LLM models to efficiently acquire and process large amounts of data. It is shown how the integration of these technologies allows for more effective and precise information acquisition, which can lead to innovative solutions in both business and science. The effectiveness of solution were evaluated using specific metrics and testing.