Text Summarisation App

What it does

Our machine learning technique would roll out a summary of each conversation in the text(every note or reply) . The text could be from any one - either the agent, or the end-user. No worries - our machine learning algorithm will roll out a summary for every conversation. We would also give out the overall summary of the entire conversation. If the agent likes the answer by our algorithm ,he can use the summary and update the ticket, or he could write out his own summary. Remember humans are intelligent than machines . :slight_smile:

How it is built:

We have trained an tensorflow model using CNN/Daily mail dataset- which contains millions of data. Since we faced a lot of challenges in the loading of the final ML model.(which requires a lot of processing) in marketplace., We have created an flask API which would load the model and serve requests and give out predictions for the text. We have hosted this external service using Ngrok to serve requests from the market place app. Coming to UI and UX , We have used technologies like javascript,html and cssto build the app. We have added an exclusive timeline for agents to know when the conversation has started and when an new event is updated in the conversation.


Training the model - Had to use CPU to finish the training, would be better if we had GPU.
Dataset - We didn’t have freshdesk data to train the model and give the real time summary.

The amazing team that developed this app: