{"id":27155,"date":"2024-03-18T05:00:00","date_gmt":"2024-03-18T04:00:00","guid":{"rendered":"https:\/\/sii.pl\/blog\/?p=27155"},"modified":"2024-03-12T10:52:41","modified_gmt":"2024-03-12T09:52:41","slug":"delivering-24-7-self-service-support-with-atlassians-virtual-agent","status":"publish","type":"post","link":"https:\/\/sii.pl\/blog\/en\/delivering-24-7-self-service-support-with-atlassians-virtual-agent\/","title":{"rendered":"Delivering 24\/7 self-service support with Atlassian’s virtual agent"},"content":{"rendered":"\n

Nowadays, chatbots are present in many sectors of the economy, and their use and interaction with them are no longer a surprise to us. Given their increasing participation and development, we \u2013 consumers or users \u2013 increasingly interact with them.<\/p>\n\n\n\n

Chatbots, implemented some time ago, have had their renaissance and downfall. However, recent years and even months of developments in artificial intelligence (AI) and natural language processing (NLP) tools have provided us with capabilities we have not experienced before, such as natural language understanding.<\/p>\n\n\n\n

Until now, the perception of chatbots was that we would not get anything relevant done through them, we would not get the information we needed, and we could only follow a path pre-programmed by administrators. The ability of chatbots to understand natural language and user intent takes the experience to the next level. This simplifies data feeding, and larger data sets can be analyzed to provide more accurate answers. Chatbots of the old type, relying on static buttons and responses, could cause frustration for users.<\/p>\n\n\n\n

Thus, the traditional support model, overloaded with repetitive tasks and long waiting times, forces IT departments to look for changes in the processes or tools used. With increasingly sophisticated chatbots, not only is satisfaction with the chatbots growing, but so are our demands on them.<\/p>\n\n\n\n

In the article, I will introduce the possibility of using a virtual agent from Atlassian.<\/p>\n\n\n\n

Atlassian Assist \u2013 virtual agent for Slack<\/strong><\/h2>\n\n\n\n

Imagine having an easily accessible support assistant who can answer your questions, solve fundamental problems, and guide you to the resources you need, all within a familiar communications platform.<\/p>\n\n\n\n

This is precisely what JSM Virtual Agent offers. At the end of 2023, Atlassian introduced Virtual Agent, a chatbot based on artificial intelligence and natural language processing capabilities. This solution has been implemented into the Jira Service Management product, an ITSM (IT Service Management) tool.<\/p>\n\n\n\n

Service management teams tasked with servicing users can free up their resources from tasks they spent a lot of time on and focus on higher priority or more complex tasks. The solution may be integrated with Slack when writing this article, but it should also be available to MS Teams users later this year.<\/p>\n\n\n\n

Atlassian Assist \u2013 what can it do?<\/strong><\/h2>\n\n\n\n

One possible function is for the virtual agent to immediately answer questions about various IT services, policies, and procedures. Using the information contained in Confluence pages, the virtual agent helps users to get the right guidance or details about their queries, which results in agents having more time to deal with more complex tasks, such as system failures or application errors.<\/p>\n\n\n\n

The agent can act as a knowledge portal, directing users to relevant knowledge base articles, tutorials, and internal resources. When we configure the appropriate paths, we will enable users to resolve minor issues themselves. In addition, the virtual agent’s responses can be personalized, enhancing the user’s sense of individuality when meeting with the virtual agent.<\/p>\n\n\n\n

Integration with popular communication tools like Slack or MS Teams allows users to receive help right where they are currently working; they don’t need to log on to another service or website. They receive help exactly where they would expect it; the agent is another ‘person’ they interact with.<\/p>\n\n\n\n

What is needed to install the agent<\/strong><\/h2>\n\n\n\n

Below, I will outline how easy it is to deploy the agent to our service, how to configure it, and how to feed it with data so that it solves the simplest scenarios that support teams have to deal with when handling the services entrusted to them.<\/p>\n\n\n\n

What is needed for this integration:<\/p>\n\n\n\n