{"id":11868,"date":"2025-06-12T08:00:37","date_gmt":"2025-06-12T06:00:37","guid":{"rendered":"https:\/\/edihadria.eu\/?p=11868"},"modified":"2026-08-18T18:43:35","modified_gmt":"2026-08-18T16:43:35","slug":"digitalni-asistent-za-korisnicku-podrsku-u-ris-d-o-o-uz-podrsku-edih-adria","status":"publish","type":"post","link":"https:\/\/edihadria.eu\/en\/digitalni-asistent-za-korisnicku-podrsku-u-ris-d-o-o-uz-podrsku-edih-adria\/","title":{"rendered":"Digital customer service assistant in RIS d.o.o. with the support of EDIH Adria"},"content":{"rendered":"<p><strong>Challenges<\/strong><\/p>\n<p>RIS d.o.o. as a technology company specialized in business software development, operates with numerous users who send daily inquiries, technical questions and requests for support. Although the company already uses classic customer service tools, such as e-mails and phones, an increasing number of queries \u2013 many of which are repetitive and routine \u2013 place a heavy burden on technical staff.<\/p>\n<p>This condition results in prolonged response time to more complex demands, reduced efficiency and the risk of user dissatisfaction. In addition, there is a need for better internal organisation of the processing of user requests, better availability of information and greater degree of automation in order to reduce reaction time and ensure a high level of service.<\/p>\n<p><strong>Solutions<\/strong><\/p>\n<p>In order to respond to these challenges, RIS d.o.o. has joined the program <em>Test Before Invest<\/em> in cooperation with the EDIH Adria team. The aim of the test was to examine the possibilities of using advanced AI-based solutions, in particular with the help of large language models (LLM) and the Retrieval-Augmented Generation (RAG) technology.<\/p>\n<p>Through the testing process, a functional prototype of a digital assistant was developed, which simulated real user scenarios in a limited environment. The assistant was integrated with a small knowledge base of the company, including FAQs, instructions for using the software and examples of user queries, and demonstrated the following functionalities:<\/p>\n<ul>\n<li>Automatic classification and prioritization of incoming emails<\/li>\n<li>Search for relevant content from internal documents<\/li>\n<li>Generate suggested responses that can be approved or edited by the agent<\/li>\n<li>Interface for visualization of communication and review of previous interactions<\/li>\n<\/ul>\n<p>Particular attention is paid to data security and the preservation of the privacy of business information, which is extremely important for RIS given the sensitive nature of user data.<\/p>\n<p><strong>Results and Benefits<\/strong><\/p>\n<p>Testing of the prototype has brought numerous insights and showed concrete benefits that could be achieved by implementing such a solution in everyday work. The most important benefits include:<\/p>\n<ul>\n<li>Significantly <strong>Reducing the burden on customer service<\/strong>, since the AI system could automatically download a large part of routine queries<\/li>\n<li><strong>Accelerating the response to users<\/strong>, in particular for simple and repetitive information and technical guidance<\/li>\n<li><strong>Increasing Customer Satisfaction<\/strong>, because the system would be available 24\/7 and allow for prompt responses<\/li>\n<li><strong>Greater internal efficiency<\/strong>, as employees can devote more time to more complex technical challenges and product development<\/li>\n<li><strong>Consistency of response<\/strong>, since the AI system always uses the same validated sources of knowledge<\/li>\n<li><strong>Solution scalability<\/strong>, which can be easily adapted to more users and new scenarios without a proportional increase in the number of employees<\/li>\n<\/ul>\n<p><iframe title=\"EDIH ADRIA - RIS TBI demo\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/gLZBxpYUWkc?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\"><strong>Lessons learned<\/strong><\/p>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">The project has shown that the implementation of advanced AI systems in customer support is not only a technical challenge, but also an organizational one. Key lessons include:<\/p>\n<ul style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Scope of application to be defined in advance \u2013 AI assistant works best in clearly structured domains with predictable queries<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">The quality and up-to-dateness of the knowledge base is crucial for the accuracy of the response<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Initially, it is necessary to involve people as supervisors who can edit answers before sending, in order to avoid inaccuracies<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Interoperability with existing support systems, such as CRM tools, user bases and ticket tracking tools, is essential<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Users must be aware of the possibilities and limitations of AI assistants, in order to facilitate their use<\/li>\n<\/ul>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\"><strong>Measurable data<\/strong><\/p>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Based on testing and simulations, the following potential impacts were assessed:<\/p>\n<ul style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Reducing the burden on employees by 50-60%\u00a0in query processing operations of lower complexity<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Shortening the response time by more than 70%\u00a0on typical, repetitive queries<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Reduction of the total number of escalations towards higher technical support by up to 40%<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Increasing the availability of support to 24\/7, without the need for additional staff recruitment<\/li>\n<li style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Improve the accuracy of responses by linking to validated documents and reducing subjective errors<\/li>\n<\/ul>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\"><strong>Conclusion<\/strong><\/p>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">Through collaboration with EDIH Adria team, RIS d.o.o. has successfully tested an advanced AI solution that can revolutionize the way customer support is provided. Although it is a prototype, testing has shown clear potential for transforming business processes, increasing operational efficiency and strengthening customer relationships.<\/p>\n<p style=\"--tw-scale-x: 1; --tw-scale-y: 1; --tw-scroll-snap-strictness: proximity; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgb(59 130 246 \/ .5); --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-shadow: 0 0 #0000; --tw-shadow: 0 0 #0000; --tw-shadow-colored: 0 0 #0000;\">The following steps include a detailed analysis of the functional requirements, the development of technical documentation for the development of the production version of the assistant and the definition of a strategy for its integration into everyday work. With this project, RIS d.o.o. confirms its focus on innovation and uses artificial intelligence to strengthen competitiveness in the digital economy.<\/p>","protected":false},"excerpt":{"rendered":"<p>Beneficiary: RIS d.o.o.<\/p>","protected":false},"author":6,"featured_media":11869,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[72],"tags":[74],"class_list":["post-11868","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-success-stories","tag-chatbot-asistenti-za-prodaju-i-usluge"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Digitalni asistent za korisni\u010dku podr\u0161ku u RIS d.o.o. uz podr\u0161ku EDIH Adria - Digitalizacija Jadranske Hrvatske<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/edihadria.eu\/en\/digitalni-asistent-za-korisnicku-podrsku-u-ris-d-o-o-uz-podrsku-edih-adria\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Digitalni asistent za korisni\u010dku podr\u0161ku u RIS d.o.o. uz podr\u0161ku EDIH Adria - 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