{"id":700399,"date":"2025-08-20T17:35:23","date_gmt":"2025-08-20T15:35:23","guid":{"rendered":"https:\/\/www.devoteam.com\/expert-view\/multi-agent-ai\/"},"modified":"2025-09-17T15:49:00","modified_gmt":"2025-09-17T13:49:00","slug":"multi-agent-ai","status":"publish","type":"expert-view","link":"https:\/\/devoteam.info\/be\/expert-view\/multi-agent-ai\/","title":{"rendered":"Guide on Multi-Agent AI: The Future of Conversational Systems?"},"content":{"rendered":"\n
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Written as part of our AI Upskilling Program<\/strong><\/h2>\n\n\n\n

This article was created as part of the Global Devoteam AI Upskilling Program<\/a>, where employees share their knowledge to accelerate their learning. The program’s key objective is to provide a foundation in AI for every employee and apply these new skills in our work. Do you want to work with us? Check out our career opportunities.<\/p>\n\n\n\n

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Career Opportunities<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

<\/a>The latest generation of AI models like Google Gemini and OpenAI’s GPT have transformed how we interact with information, but a new challenge has emerged because most users want AI to solve more complex tasks. When data is scattered across different formats\u2014from PDF contracts to Excel spreadsheets\u2014a single AI model often falls short. This is where a powerful new solution, multi-agent AI architecture<\/strong>, is stepping in.<\/p>\n\n\n\n

Multi-agent systems create a team of specialised AIs, with each agent handling a specific task or data type. For example, one agent might be an expert in legal documents while another specialises in financial data. This collaborative approach allows the system to process diverse information with a level of precision that a single model cannot match. The concept is gaining traction because it mimics how human teams work, ensuring that the AI can understand user intent, access relevant information from varied sources, and provide accurate, fact-based answers by pairing with Retrieval-Augmented Generation (RAG)<\/a><\/strong> technology. This innovative combination ensures the AI builds responses on real, up-to-date data, rather than relying on its base knowledge.<\/p>\n\n\n\n

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How can AI models truly understand what is being asked of them if the relevant information is spread across multiple formats and contexts?<\/p>\n\n\n\n

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Diego Rubio
Data Engineer<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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What you’ll read in this article<\/h3>