Ciphix is a Rotterdam-based IT implementation company dedicated to **helping organizations unlock human potential** through smarter business process automation. With an integrated approach to RPA and Machine Learning, we’re able to offer our clients – including global brands and government organizations – **uniquely robust solutions** to their business challenges.

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RPA Solution Architect

The Get Files From Folder activity extracts the filenames within the specified folder and outputs a list containing the file paths as strings which can then be used for other activities.

The activity also provides a filter for extensions with an array as input and an option for including the full path name from the extracted filenames.

An activity that allows the user to extract all the filenames from a specified folder with filter options.

The activity uses a SVM and sorts the data in classes. This will essentially draw a line between the two generated classes of data making sure that the line provides the biggest “separation” between those two classes.

The line drawn by the SVM is then used by the activity to make a one point ahead forecast. See the image attached.

This is a custom activity that estimates a model for a discrete variable using a Support Vector Machine (SVM).

The estimated logit model describes a non-linear regression of which the goal is to perform a forecast where the variable we want to predict is either 0 or 1 (binary). The model uses a logistic probability function to determine the relationship between the dependent and the independent variables. The difference in accuracy between this logit model and a linear probability model is shown in the graphs below.

This machine learning related activity is used to estimate a model for a binary variable and uses that model to make a one point ahead forecast for the binary variable.

This activity enables you to clear a folder, this means that all sub folders and files are removed.

Practically, the whole folder is removed and recreated.

An activity that allows you to clear a directory including all subfolders

The Save Mail Attachments workflow saves all attachments in unread mail messages into a specified folder. It outputs a boolean value indicating whether an email was received. The input is an email address, an email password and the path to a folder in which the attachments will be saved.

NOTE: Installation Guidelines for Custom Activities can be found [here](https://dmtyylqvwgyxw.cloudfront.net/instances/214/assets/help-guides/UiPath-Go-Installation-Guide-Custom-Activities.pdf)

A workflow that allows the user to save all the attachments from their emails

The input values are the current Working Directory and the relative path to the Runreport from the current Working Directory. A Working Directory will be created with a copy of the Runreport in it.

Input:

\- in\_WorkingDir: The path to your current Working Directory

\- in\_RelativePathToTemplate: The relative path to the RuneReport\_Template.xlsx

Output:

\- out\_WorkingDirPl: the newly created Working Directory where a Runreport is created for auditing purposes

A workflow that enables you to create WorkingDirectory where a Runreport is created for auditing purposes.

This component checks whether or not a download is completed. The waiting time for the download can be set. The activity blocks the execution of the robot and awaits for either download completion or timeout.

Enables the user to set the ReadOnly property of a given file.

'MakeReadOnly' field determines whether or not the file (from 'FilePath') will be set to 'readonly' (='true') or not (='false'). Input in this field is a boolean.

Typing the text from the MRZ of identification cards can be tedious. With the MRZ extractor this becomes much simpler. With the help of Google Vision this activity can extract the text within the MRZ zone of identification cards. Besides the extraction this activity can also parse the MRZ text using a self build parser. This parser extracts the information which is encoded in the MRZ text and labels each portion of it.

As inputs you need to provide an image of the ID from which you would like to extract the MRZ text and a .json file containing your credentials for use of the Google Vision API. Afterwards the text extracted from the image can be found in the TextResult block. The ParseMRZ option can be set to either True or False (default: False). When set to true the ParserResult block will yield the parsed MRZ code.

An activity that allows the user to extract text in the MRZ of identification cards. It also allows for parsing of the extracted MRZ text. This however is still a prototype parser.