Soapbox Blog

In today’s fast-paced, competitive business environment , the need to resolve issues and respond to customer requests quickly has never been higher as the cost of lost productivity is enormous. According to Gartner, the average cost of IT downtime (alone) is $5,600 per minute. Whilst the cost of lost productivity varies between industry, lost productivity as a result of staff not being able to do their job whilst they wait for answers is undeniable.

Often the answer to a question is already known; captured in a knowledge article, written by a support agent, stored on one of the numerous systems that the enterprise utilises across different business functions or even across multiple groups within the same business function.

In addition to knowledge being distributed across disparate systems making knowledge difficult to access when and where it is needed; the search mechanisms employed by these systems are typically limited to simple ‘keyword’ searching. Unless you know exactly what to search for, it’s unlikely your search will yield the desired result.

To solve this, Soapbox has developed Sofi, our AI Virtual Agent, with the ability to perform intent-based searching across all of your knowledge repositories so that people can access your collective, enterprise knowledge via their own preferred channel of interaction eg Slack, Teams or service portal. Combined with Sofi’s ability to clarify a persons’ needs through conversation, Sofi is able to pin point the most relevant article (and even specific content within an article) from the appropriate knowledgebase.

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For example, let’s say that Paul, an employee, needs to understand how to make a change to a timesheet that was submitted and approved last week and he also wants to know what the negative leave policy is over the Christmas period. Paul's IT department utilises the ServiceNow knowledgebase which contains two potentially relevant articles entitled “How to modify a submitted timesheet” and “How to modify an open timesheet”. The HR department have an Atlassian Confluence page entitled “Xmas Leave Policy”.

Paul, whilst working within his collaboration tool, Slack, simple ‘asks’ Sofi:

Paul: “Sofi, I need to make a change to a timesheet”

Sofi: “Hi Paul, did you want to modify one that you have submitted or one that is still open?”

Paul: “It’s one I submitted last week”

Sofi: “Okay Paul, you will need to follow the process outlined in this knowledge article How to modify a submitted timesheet. Is there any thing else I can help with?”

Paul: “yes, I need to take time off over Christmas but I don’t think I have enough leave”

Sofi: “Let me check if you have sufficient leave”

Sofi: ”Hi Paul, I’ve checked your leave balance and confirm you would need to go into negative leave. Would you like some information on our negative leave policy?”

Paul: “Yes please”

Sofi: “ Ok, here is something that may help

Sofi: displays Intelligent Search results including “Xmas Leave Policy”.

What can we expect next in the area of AI-driven Intent-based searching? Imagine the ability to automatically identify the specific answer to a question simply by pointing Sofi at an existing knowledge article. Sofi’s AI engine will soon be able to identify question and answers pairs, building a training model to allow people to search for these answers.

To see a demonstration of our Atlassian Confluence Intelligent Search integrated with ServiceNow please visit our video, Sofi Intelligent Search for Confluence and ServiceNow using Slack. For further information on this and Sofi integrations, please contact us for a demo.

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