Speaker
Nadia Kaloyanova
Description
We are a company from the private sector and we can share our experience on what are the most common business applications of our (and in general) AI Conversational Technology and Natural Language Understanding.
Some of the most common use cases for our technology are:
- Deep Sentiment and Opinion Analysis - extract content from pdf files, web articles and video files, and analyze it to extract key topics, opinion holders, opinion targets, and sentiment expressions.
- AI Knowledge Base - using AI to transform static guides and documentation into an interactive knowledge base that provides answers to a specific user questions.
- AI Reporting - analysing data and producing on demand real time reporting for employees. E.g. The employee asks "What were our sales last month" and the AI analyses the data and gives the concrete answer "The sales for last month were 3 mln" rather than the employee having to read the sales reports and calculating it
- AI Assistants for Customer Support, making handling customer requests more efficient and helping agents be more effective. The Customer Support can also be integrated with social media channels such as Twitter, Facebook, Skype and Slack.
- Using an AI Assistant internally to automatically assign incoming customer requests/emails to the right department and monitoring the sentiment about KPIs in real time
- Easier internal case raising and updating - the AI Assistant can be integrated with the company's back-end systems and provide an easy to use interface to the employees, helping them managing tickets/cases, rather than the time consuming logging into systems like MS Dynamics, Salesforce, etc. which are confusing, difficult to use, people miss steps, etc.
Title
Conversational AI Technology - Business Applications
| authors | Nadia Kaloyanova and Martin Minchev |
|---|---|
| affiliation | . |
