Hello Mathan,

Nowadays most email servers provide sophisticated spam filtering infrastructure and the email sever takes care of getting rid of these spam emails in most cases. A lot of the popular providers also rely on machine learning techniques and keep their spam filtering algorithms upto date so that the spam email detection is very accurate. In my opinion this is one of the common approaches to handle spam emails. 

The ones email servers can't detect are the ones that are more believable direct spam emails like the ones you mentioned. In this case I would think that you need to write custom solution to detect very targeted direct spam emails. You could also look at using text analytics and NLP techniques to get smart at detecting these direct spam emails and accordingly process them. I hope this helps.

Thanks.

Hi Jagdish,

In the "Intelligent routing" section in "Behavior" tab there is an option to create a case automatically based on conditions you could define. You could also use NLP or message headers to create conditions and case gets created automatically when the condition is evaluated to true.

Thanks.

Hi Ravikumar,

Use email service rules to manage incoming email. If you configure the email listener correctly then it monitors an email inbox on a server identified by an email server configured in the email account. When messages arrive in that inbox, the email listener routes them to an email service rule. So you need to create a email service rule and typically the service activity configured in that email service uses the information in the message to perform your logic such as create a work item. You can create a Service Email rule by selecting "Service Email" from the "Integration-Services" category in records explorer in Dev Studio.

Regarding junk mails, could you check from which email account are you getting those and what is the content of those email look like?

Thanks

Hello Shipeng Tian,

Usually size of the attachments has some impact on the overall processing time. Moreover there are also other parameters such as network latency, email connectivity with the email server could cause performance degradation. Could you please share more details around where exactly most of the time is being spent? Is the time spent while establishing the connection with email server, reading the attachments from the server, the service activity execution etc. These details would help us understand where the bottleneck is. I hope this helps.

Thanks. 

Hi Vinoth,

Thanks for asking this question.

The messages for email services are routed by email listeners. When an email listener routes a message that has files attached to it, the listener creates a page named pyAttachmentPage (of class Data-ServiceMessage) and puts the file(s) on that page, using the properties pyAttachNames and pyAttachValues.

If you want an email service to save the attached files from incoming email messages as work object attachments or use the contents of the attachments to create a work-object then configure the service activity to extract the files from the pyAttachmentPage and create the work object accordingly.

I hope this helps. Please let me know if you have any further questions.

Thanks.

Hi Omkar,

Thanks for raising this. 

It looks like the data page reference for the SMTPHost is resolved correctly as the value corresponding to Email_Server is printed correctly. But the debugging information indicates that the data page reference is not resolved. This seems like a bug. Which version of Pega are you using? is this the first time you are trying this or did it ever worked before for you?

Thanks.