We are a dynamic team and our passion is to successfully implement modern solutions and technologies for companies. What are the trends that will cause future change by digitising the world of work and business? We want to play an active part when it comes to shaping the digitisation and the workplace of the future. We collaborate with various experienced and internationally acclaimed software vendors with whom as implementation partner we help you to get the most out for your business. Therefore we work with technologies in the field of Robotic Process Automation (RPA) on personal robot assistants (PRA) and Artificial Inteligence (AI).

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Managing Director

Head of Delivery Germany

This activity saves a given mail attachment object to a file.

A mail attachment object can be retrieved by accessing the mail attachment collection from a single mail object.

Individual filtering can be applied by the developer prior to calling this activity so only important attachments will be saved.

Saves a given Mail attachment object to file.

Contains Activies for copying and moving directories.

You are able to allow overwrite of files and moves the complete directory with subfolders.

With these activities folders can be copied or moved to a different drive.

Contains Activies for copying and moving directories which includes different drives.

Checks if the given folder contains another file or folder in it

**In Arguments**

· in\_Beautify - Optional. Default: True

Will output only the messages

· in\_ExecutionStartedIdentifier - Optional. Default: "execution started"

· in\_LogFileUiPathPath - Optional. Default:

Environment.ExpandEnvironmentVariables("%LocalAppData%/UiPath/Logs/")

  

**Out Arguments**

· Out\_CustomLogfilePath - Output Path of the newly created Excel Logfile.

The created UiPath LogFile is “beautified” and written into an Excel-File

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With this activity, it is possible to use fuzzy logic without the need to implement code or worry too much about the implementation of the algorithms.

  

For the **advanced version** of this package, please check this page: [https://marketplace.uipath.com/listings/3081](https://marketplace.uipath.com/listings/3081).

  

All dependencies are bundled within the package - so it is easy to use and understand.

  

Compute the Jaro-Winkler, the NGram and the Levenshtein distance between two strings to help you **determine how similar two strings are**. This can be used to **validate inputs** and check if there might be a typo, for example when checking master data in an OCR process.

It is also possible to leverage the Lucene.net library.

  

The activities contained in this package allow you to **compare strings** and as a result, **get the similarity between the strings by using different methods**! Links to the explanations for the different methods are included in the user manual.

  

The activities included are:

*   GetJaroWinkler Distance
*   GetLevenshtein Distance
*   GetNGram Distance
*   LuceneSearch Strings

With this activity, it is possible to use fuzzy search logic without the need to implement any code.

With this activity it is possible to add or substract an integer from a column character to receive the matching column in Excel.

For example if you add 5 to the column "A" the result would be "F"

With this activity it is possible to add or substract an integer from a column character to receive the matching column in Excel.

**What is Petze?**

Petze is a revolutionary RPA code reviewer that will help and guide you in all your RPA implementations.

We have automated RPA Code Quality Assurance making it easier than ever to ensure that no automation fails in production.

By simply dragging your UiPath project into Petze, you are connected to the Roboyo Knowledge Base which gives you an explanation of each best practice as it is evaluated in real time. This allows developers to be trained as they go along, speeding up the RPA learning curve.

For example, is there a hardcoded password creating a potential security breach? Petze will flag it! Are the naming conventions not followed properly, thus decreasing code re-usability? Petze will flag it!

Petze is also configurable which allows you to enable and disable specific best practices at will and ultimately tailor them to your reality.

  

**Who is it for?**

[Delivery Team](https://www.roboyo.de/en/roboyo-cloud/petze/) - Developers and solution designers can now validate their UiPath workflows in real time, and benefit from our Roboyo Knowledge Base. An error report is produced every time Petze runs ensuring that no error is left behind, thus increasing code quality and minimizing the need for code troubleshooting.

[Operations Team](https://www.roboyo.de/en/roboyo-cloud/petze/) - Release Managers can now approve a process to production without having to be technically savvy in UiPath. By requesting an error-free report, one can now be sure that all best practices are respected. Additionally, an error history panel allows Operations to see development progress, adding an extra layer of visibility which allows for better resource planning.

[Management Team](https://www.roboyo.de/en/roboyo-cloud/petze/) - Petze has also been prepared for managers. Would you like to know the progress of your team in real time? Petze aggregate statistics to create reports showing the progress of each automation in scope, creating full transparency for non-technical stakeholders on the progress of the delivery team.

  

**Key Features**

[Checker](https://www.roboyo.de/en/roboyo-cloud/petze/) – The checker is an individual best practice that Petze is actively validating in the source code in the scope of the analysis.

[Drag & Drop](https://www.roboyo.de/en/roboyo-cloud/petze/) - By simply dragging an UiPath project onto Petze, the quality checking is started automatically without any additional command.

[Reporting](https://www.roboyo.de/en/roboyo-cloud/petze/) - Technical and non-technical error reports can be created with all explanations, allowing developers or managers to approve a process to production.

[Project History](https://www.roboyo.de/en/roboyo-cloud/petze/) - Reports generated by Petze are recorded in a Project History, allowing developers and managers to track the progress of each code review.

[Release Management](https://www.roboyo.de/en/roboyo-cloud/petze/) - Petze has multiple “Review and Acceptance” features to allow for different Release Management rules.

[Checker Configuration](https://www.roboyo.de/en/roboyo-cloud/petze/) - Petze offers a Tenant Administration feature allowing multiple business units to have different types of checkers depending on how best practices need to be applied.

Petze is a revolutionary RPA code reviewer that will help and guide you in all your RPA implementations.

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The downloadable skill and ML model which was developed by Roboyo in cooperation with DatasparQ will provide **a good base level of performance for emails/text in one language** (English or German). 

  

The model needs to be trained before first use and the “buckets” the model must use to classify the given emails/texts need to be clear and supplied in the training set. After the deployment the skill can be used directly in UiPath Studio to classify any text supplied as a string - no fiddling around with JSON or REST calls needed! 

  

The model gives back a confidence score based on which you can decide on how to proceed with the classification. Is the confidence too low? Send it to the action center and let a human classify the correct bucket and feed the results back for retraining the model!

  
This model is a great starting point for using AI Center to sort and classify text directly out of the Studio and then through your robots with ease! However, we understand that real-world use cases are often more complicated. Emails come in different languages and may require mapping to hierarchical classifications. Additionally, the measure of success for a classifier will vary across different use cases.

  
If you have further needs for this model, please get in touch with us by opening a question on this listing page and we will get back to you!

This AI Center model will classify emails according to their contents based on buckets that are given to it by supplying appropriate training data.

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The KPI Monitor is a package that tracks KPIs on the fly without the need to rely on variables or arguments within workflows.  
It allows saving the KPIs to various data storages like SQL, any API (Json-Format without authentication, post request), XML, or JSON files.

All common KPI types are supported, like time tracking with a stopwatch, string, bool, number or datetime values.

With this package, it is possible to seamlessly track different KPIs at different stages of the process without relying on third-party products. The biggest advantage of the library is that tracking is independent of variables and is therefore much easier to implement, change and maintain the KPIs.

The values are either tracked in memory or a CSV file.

It was never this easy to track KPIs for processes in production or even track milestones while testing a new process with unmatched flexibility for the output.

The KPI Monitor is a package that tracks KPIs on the fly. It allows to track the KPIs in various data storages like SQL, any API, XML files or JSON files.