![]() ![]() We then added the ability to check if you had already stated the company (and if not, ask that question). As we added more and more phrases, it became much more reliable at capturing your name. Initially, you had to respond with an exact phrase otherwise it just terminated the call. So we asked who was calling and then created a task called identify_caller and started inputting all the possible responses we could think of such as “This is ”. ![]() We started by looking at our existing “Create Issue” form that we currently use, and stripping it right down to the minimum.Ī task can be set to listen after it has been triggered and the result is stored in a field variable. We therefore needed to construct a conversation that collected the information required to create a Jira issue. Our aim for the chatbot was to remain as close to a natural conversation as possible – we really did not want the whole “press 1 for X” dialog. This seemed perfect, so Tom spent some time becoming more familiar with the tools and running through the “Getting Started” tutorials, showing the rest of the team how easy it was to create a functional model. ![]() It provides support for voice calls via phone or Amazon Alexa, GoogleVoice, as well as text via SMS, Slack etc. ![]() The more phrases you have mapped to a task, the better the model becomes. So in the basic example they define a task “tell_joke” which would be triggered by the input “hey, tell me a joke”, “make me laugh” etc. They have a number of API’s one of which is called AutoPilot which allows you to define tasks and phrases that will trigger those tasks. Tom found Twilio, who provide tools for natural language processing and text to speech. We wanted this bot to be equipped to handle incoming support calls, capture the relevant details and raise an appropriate JIRA ticket for the team to investigate. We wanted to see if a chatbot could improve this experience for our customers. One issue we sometimes have on the support desk is capturing comprehensive and accurate information on the problem being reported. We created a team from our crack Support desk squad- Toby Catlin, Tom Brook and Andy Fernandes. The theme for Hackday XI was ‘Talking with Robosaurs’ – a focus on artificial intelligence and communication. ![]()
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