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Community Blueprints are tried-and-tested examples of automation projects, created by our community members. You can submit your own project to the Blueprints library here.

Refactoring UiPath Bot to Blue Prism with Capture Assistance

Which industry did you deploy this use case in?

  • Financial Services

Which functional area / department within the organization benefitted most from this automation?

  • Finance

Which SS&C Blue Prism tools did you use?

  • SS&C Blue Prism Enterprise
  • Capture
  • Desktop

Describe the problem your automation aimed to solve

The automation was motivated by the company's need to optimize costs related to UiPath licenses, which were high. Faced with the availability of existing SS&C Blue Prism licenses, we made the strategic decision to migrate some of our robots, requiring significant refactoring.

This transition resulted not only in a noticeable reduction in operational costs but also in substantial gains in efficiency in the processing time of each robot item. 

The shift to SS&C Blue Prism not only met budgetary demands but also significantly enhanced the overall effectiveness of automation, promoting a more efficient and cost-effective approach to executing automated tasks.

Provide a brief, step-by-step outline of how you set up your automation


We began the process by focusing on understanding the scope through existing UiPath developments and available documentation. Once the process scope was defined, a thorough review was conducted in collaboration with business users to identify any gaps left by the previous solution. Additionally, we utilized the Blue Prism capture tool for enhanced efficiency in process mapping, resulting in significant time gains. It's noteworthy that SEFIP data was frequently generated in Excel spreadsheets by the business area for the robot's consumption.


The solution was designed using Blue Prism as the main platform, complemented by the strategic use of Excel to feed the queues. The process was divided into three distinct stages:

SEFIP Software:

•    Responsible for registering employees and companies, covering all months and retroactively spanning 5 years.
•    Generation of the .SFP file to feed the queue for the second process.

CAIXA Portal:

•    Uploading the .SFP file generated in the first process.
•    Registering with the vendor base, spanning all months and retroactively covering 5 years.
•    Generating a final file to feed the queue for the last portal.

ELAW Portal:

Comprehensive processing of all cases, including analysis, file compression, and consolidation into a single file.

Efficient submission to the ELAW portal, resulting in a significant improvement in processing speed and ensuring greater security. Excel spreadsheets generated by the business area played a crucial role during various phases of the process.


The process and its subprocesses were automated using Excel for information manipulation from SEFIP, as well as interaction with CAIXA and ELAW portals. After generating and analyzing employee and company records, the data were sent to the portals for processing. During this flow, we implemented robust traceability to ensure each step could be monitored. Excel spreadsheets, generated by the business area, were a primary data source for the robot during the construction process.

Quality Assurance:

During development, we conducted a comprehensive testing approach to ensure project quality. This included:

  • Unit Testing:
    Carried out during development to ensure each component and activity occurred successfully.
    Focus on validating individual functionalities for effectiveness.

  • Integrated Testing:
    Conducted to ensure proper harmony and integration among different components of the system.
    Verification that subprocesses interacted efficiently and data flowed correctly between stages. Excel spreadsheets generated by the business area were especially monitored during these integrated tests.

  • Internal Approval:
    Internal reviews were conducted to ensure the project met established requirements and standards.
    Identification and correction of any issues or gaps during the early stages of development, including proper integration of Excel spreadsheets into automation.

  • User Final Approval:
    Involved active participation from end-users for practical system evaluation.
    Collection of valuable feedback for continuous refinement of functionalities, including effective interaction with Excel spreadsheets.


The project implementation occurred smoothly, and to ensure a seamless transition, go-live sprints were conducted. These sprints were designed to closely monitor system performance and evaluate key indicators, allowing for continuous analysis of deliveries and identification of areas for improvement. Excel spreadsheets generated by the business area were fully incorporated into the delivery process, ensuring that the robot could consume them efficiently and accurately during production environment operation.

What were the main challenges you faced during this project, and how did you overcome them?

During this project, we faced the crucial challenge of gaining acceptance from the finance team for our improvement proposals. We aimed to optimize operational efficiency and address gaps in the previous tool, UiPath.

To overcome this, we conducted a detailed analysis of financial processes, identifying points of inefficiency and shortcomings. We developed proposals based on concrete data, highlighting measurable gains.

This technical and collaborative approach was pivotal for the successful implementation of changes, resulting in enhanced efficiency and addressing identified gaps.

What was the impact of your project?

The project had a significant impact on optimizing operational efficiency and addressing identified gaps in the previous tool, UiPath. The implementation of the proposed improvements resulted in more efficient and measurable financial processes. Tangible gains were observed in terms of speed, accuracy, and operational cost reduction.

Furthermore, the technical and collaborative approach employed facilitated acceptance from the finance team, ensuring a smooth and effective transition to the implemented changes. The practical application of detailed analyses and data-driven proposals contributed to a more robust operational environment aligned with the organization's efficiency goals.

In summary, the project's impact was positive, bringing substantial improvements to financial processes, strengthening operational efficiency, and establishing a solid foundation for more effective operations in the future.

Do you have any advice or learnings from this project to share with the community?

Certainly! Something important the community should know about our Blueprint is the significance of continuous collaboration and communication with the involved teams. Throughout the project, the technical and collaborative approach was crucial in overcoming challenges and ensuring acceptance of the proposed improvements.

Furthermore, I emphasize the relevance of a detailed analysis of specific processes and grounding proposals in concrete data. This not only strengthens the validity of the suggestions but also provides a solid foundation for measuring the impact of implemented changes.

The application of continuous monitoring tools, such as dashboards and key performance indicators, can be valuable to ensure that improvements continue to bring measurable benefits over time.

In summary, collaboration, a data-driven approach, and continuous monitoring are key elements for success when implementing a similar Blueprint. These are principles that can be valuable for others deciding to try the same Blueprint in their own projects.


Like this Community Blueprint? Be sure to click the "Recommend" button to reward the author! You can also ask the author questions about this Blueprint by clicking "Reply".

Wagner Vasconcelos
Analista de Inteligência Operacional Sênior
Via Varejo


Thank you Wagner for the excellent summary!


Jack Look
Sr Product Consultant
Blue Prism
Community Team
Community Team

@wagnervasconceloos this is so detailed, and such a good story. Thanks so much for sharing!

One question from me is around the refactoring / redesign piece. You mention overall efficiency gains after the project was complete, how did you deliver that through the redesign? What was missing from the original automation that you corrected?

PS - I absolutely love how you reinforce the value of collaboration here 💙

💙 Michael
(I'm part of the SS&C Blue Prism Community Team)

You're welcome! I'm glad I could provide a helpful summary for you. If you have any more questions or need further clarification, feel free to ask.

Wagner Vasconcelos
Analista de Inteligência Operacional Sênior
Grupo Casas Bahia

Hi Wagner
What was the biggest challenge during the migration process?
Congratulations on the project!!

Leonardo Soares
RPA Developer Tech Leader
Bridge Consulting

Thank you for appreciating my story!

The significant efficiency improvement in the refactoring/redesign project was achieved through close collaboration with the business area. During the analysis of the previous automation, we identified some gaps in the navigation of certain steps. By working together with the business team, we understood that there was a more effective and faster way to access certain navigation contexts within the application.

Building on this insight, we implemented strategic changes in the redesign, optimizing the interaction between the robot and the application. This collaboration was crucial to address the gaps in the original automation and resulted in noteworthy efficiency gains upon project completion.

Wagner Vasconcelos
Analista de Inteligência Operacional Sênior
Grupo Casas Bahia

Thank you for the positive feedback, Leonardo!

I'm glad you liked my project.

The biggest challenge during the migration process was undoubtedly ensuring that the processing time for each employee case was minimally equalized. In UiPath, the average was 11 minutes per case, and with the transition to Blue Prism, we were able to reduce that time to 9 minutes. Although the gain was not very high at low volume, considering the high volumes of data, we were able to scale the saved hours effectively.

Wagner Vasconcelos
Analista de Inteligência Operacional Sênior
Grupo Casas Bahia

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Last update:
‎10-06-24 08:40 AM
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