{"id":4516,"date":"2025-05-20T14:04:00","date_gmt":"2025-05-20T17:04:00","guid":{"rendered":"https:\/\/matrixgo.ai\/evolucao-funcionarios-digitais\/"},"modified":"2025-05-20T14:04:00","modified_gmt":"2025-05-20T17:04:00","slug":"evolucao-funcionarios-digitais","status":"publish","type":"post","link":"https:\/\/matrixgo.ai\/en\/evolucao-funcionarios-digitais\/","title":{"rendered":"Automated + Humanized Service: Understand the evolution of digital employees"},"content":{"rendered":"

If your company still associates digital service <\/strong>only to those messages standardized <\/strong>like \u201cPress 1 to talk to\u2026\u201d, it\u2019s time to meet a new scenario.<\/strong> THE technology <\/strong>evolved, and with it emerged the digital employees<\/strong>, solutions that unite automation <\/strong>and intelligence <\/strong>to transform the experience <\/strong>of the client.<\/p>\n\n\n\n

In this article, you will understand how customer service has evolved from Traditional URA<\/strong> for the artificial intelligence agents (LLMs)<\/strong>, where each one works best, and how the Matrix Go<\/strong> delivers both solutions <\/strong>so that your enterprise <\/strong>choose what makes the most sense.<\/p>\n\n\n\n

How it all began: from IVR to artificial intelligence<\/strong><\/h2>\n\n\n\n

THE URA (Auditory Response Unit)<\/strong> was one of the first forms of automated service<\/strong>. Originally created for organize <\/strong>and speed up <\/strong>phone calls, it continues to be extremely <\/strong>useful to solve demands <\/strong>simple in form fast <\/strong>and direct. They were even adapted to the initial digital service menu.<\/p>\n\n\n\n

Already the LLMs (Large Language Models)<\/strong> represent a new generation of technology<\/strong> in the service. With Advanced AI<\/strong>, they are able to to understand <\/strong>what the customer wants, respond with empathy <\/strong>and keep a conversation going natural<\/strong>, as a human <\/strong>would.<\/p>\n\n\n\n

Each of these solutions <\/strong>has its space. While the traditional menu <\/strong>shines on the phone with high call volume and in direct use in service menus, LLMs <\/strong>deliver more interactions customized<\/strong>.<\/p>\n\n\n\n

READ ALSO: <\/strong>Intelligent Automation: The Future of Business Productivity<\/strong><\/a><\/p>\n\n\n\n

What is auto attendant and where is it extremely useful?<\/strong><\/h2>\n\n\n\n

THE URA and traditional menus<\/strong> are a classic example of automation <\/strong>node service<\/strong>. When a customer, for example, calls a enterprise <\/strong>and listen commands <\/strong>as \u201cPress 1 for technical support\u201d, is interacting <\/strong>with a URA<\/strong>.<\/p>\n\n\n\n

That technology <\/strong>is efficient, fast <\/strong>and ideal for organize available commands and services<\/strong>, especially in operations large volume<\/strong>It directs customers to the right department, offers straightforward options, and allows for simple problem-solving without the need for a human agent.<\/p>\n\n\n\n

Furthermore, the automatic service <\/strong>has low operating costs and works very well in repetitive demands<\/strong>.
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READ ALSO: <\/strong>ChatGPT: discover features that make a difference! \u2013 MatrixGo<\/strong><\/a><\/p>\n\n\n\n

The arrival of LLMs: automated + humanized service<\/strong><\/h2>\n\n\n\n

With the evolution of models of natural language<\/strong>, like the LLMs (Large Language Models)<\/strong>, new ones have emerged possibilities <\/strong>for the digital service<\/strong>. Unlike traditional automation, which works with limited commands<\/strong>, an agent of LLM <\/strong>is capable of understand the customer's real intention<\/strong>, keep a conversation going fluid<\/strong>, empathetic and even proactive<\/strong>.<\/p>\n\n\n\n

Imagine the difference:<\/p>\n\n\n\n