March 14, 2021

Email classification with the help of AI and RPA - Deep Dive

After having shared the email classification video, I got a couple of requests to show the details of the flow. 

I have now recorded the video below:




It all starts by checking the messages coming with a specific subject and from a specific email address. I put those requirements so that the automation reacts only to those emails and nothing else. With the delay and the loop, I let the process run all the time and wake up when those specific emails come in to the mailbox. 

Then, by using Microsoft translator cognitive service, I am translating the emails to English since the ML model has been built only to classify the emails in English. Adding this activity removes this limitation.




By using the "emailclassification" ML skill, the system evaluates the content of the translated email (if it is a non-English email) and comparing the confidence score, which I set deliberately pretty low, it classifies it and moves it to the corresponding email folder.

Alphabet.Workflow.Activities gives me the possibility to update the subject of the email with the translation. For the moment, the activity only updates the subject and not the body and this is why I am doing the update on the Subject level.






The Message Boxes used in the flow are there just for the demo purposes and removing them makes the flow run quicker and without a human interaction.

Hope you find this useful.

Next week, I will focus on the human interaction part in more details as the robots might need to get some confirmation from time to time, especially when they are not sure with the outcome, for instance when reading a document. You can instruct the robot to use document understanding framework and also put a confidence score if a ML model is required. For any score below the confidence score, you might want the robot contact a human to get his/her approval. This is a recommended way to proceed when using the framework, especially in the beginning. The good thing is that you can use the human input to train the ML model. 

This setup, I mean using RPA-AI and Human, opens new doors and gives you the possibility to build very complicated flows.

See you next week !









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