Robotic Process Automation (RPA) is a form of automation technology that uses software robots or “bots” to perform tasks within digital systems. These bots are programmed to mimic the actions that a human user would take when interacting with computer applications and systems, such as data entry, data extraction, form filling, and more.

RPA is used in a wide range of industries and processes, including:

  • Data entry and data migration
  • Invoice processing and accounts payable
  • Customer service and support
  • HR and payroll processing
  • Supply chain and logistics
  • Healthcare claims processing
  • Financial services and banking
  • Reporting and analytics

Process Steps:

  • Process Identification: Identify and select the processes that are suitable for automation. Typically, these are repetitive, rule-based tasks with a digital interface.
  • Bot Development: Develop bots using RPA development tools. Bots are configured to interact with applications and systems just like a human user.
  • Bot Deployment: Deploy bots into the target environment where they will perform the automated tasks.
  • Execution: Bots execute tasks according to the predefined instructions. They can work around the clock without breaks and are highly accurate.
  • Monitoring and Control: An RPA orchestrator manages the execution of multiple bots, monitoring their performance and handling exceptions.
  • Data Integration: Bots can integrate with data sources and databases to input or extract information as needed.

Lab integration work flow


BR Public Laboratories

What We Did

Full data capture and exams process integration

Data Entry Automation: Implement RPA bots to automate the process of data entry from various sources into our laboratory information management system (LIMS). This includes the input of test results, sample information, and other relevant data.

Lab Software Integration: Integrate the RPA system with our existing lab software, ensuring that data is accurately and efficiently transferred between systems. This includes compatibility with the LIMS, analytical instruments, and other software used in our lab.

Error Reduction: Minimize errors and discrepancies in data entry and transfer, thereby improving data accuracy and reducing the risk of manual entry mistakes.

Operational Efficiency: Streamline data management processes, reduce the time required for data input, and enhance the overall efficiency of lab operations.

Scalability: Design the RPA system to be scalable, allowing for the automation of additional processes and tasks in the future as needed.