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Cognitive Automation

Cloud RPA With Generative AI

Dr. Jagreet Kaur Gill | 02 September 2024

Cloud RPA

Introduction RPA on Cloud Architecture

RPA onCloud Architecture means, how the RPA bot is performing on the cloud architecture. RPA cloud architecture is the process of RPA bot integrating into cloud architecture. Nowadays, every organization is moving towards Cloud and automation for better productivity. RPA bot automates the business processes on the cloud platforms. Cloud platforms such as GCP (Google cloud platform), Azure (Microsoft cloud), AWS (Amazon cloud), etc. These clouds platform adopting Robotic Process Automation to automate Business Repetitive tasks to increase productivity, saving time, decrease human intervention, etc.

RPA is just one component of a broader intelligent automation platform that must be combined with other automation technologies. Source: RPA- What's in Store for Future?


RPA bot integrates into the cloud platform through Cloud compute engines (EC2 in AWS). Cloud administration provides the computing machine to the RPA bot to perform automation, Cloud Services to the RPA bot, and the RPA bot platform. Cloud Provides services to organizations to store data. They provide their own data storage (RDS in AWS). RPA bot will run on cloud infrastructure as it runs on the local machine.

How to Implement Robotic Process Automation on Cloud?

RPA on Cloud implementation requires a cloud platform and a developed RPA bot. When an RPA software engineer developed the RPA bot, the bot will be deployed to the cloud platform to perform the automation. RPA automation performs on the cloud by using cloud services such as RPA on the cloud is also called RPA as a service(RPAaaS) because it works as a service for the cloud's platforms and automates the tasks. Example :
  • If we want to access google sheet on google drive to access the sheet data, we must Google Cloud Service to perform the task.
  • Accessing AWS management data in excel can be performed through an RPA bot with efficient and correct data extraction, and we can manipulate it according to requirements.

With RPA Tools, we get a virtual employee who can perform repetitive activity faster and more cost-effectively than humans.Taken From Article, 3 Best RPA Tools: Picking The Right RPA Tool

How does an RPA bot work?

  • The first step is choosing the right cloud platform with the correct RPA tool to achieve a better business solution.
  • RPA technology provides the bots to perform the process without human intervention. RPA bot integrates into clouds through Cloud compute engines(EC2 in AWS).
  • To perform RPA on the Cloud, we require both RPA platforms (Any RPA tool such as Uipath, Blue Prism, Automation Anywhere) and cloud Platforms (Any cloud Aws, Azure, etc.)
  • Install RPA tools to the compute engines of the Cloud.
  • RPA bot can access cloud services like to store data, manipulate it, etc.
  • The process will automatically run at the scheduled time to the cloud platform. RPA technology stores all bot details in a single place(Orchestrator). If Bot execution fails, the user can quickly identify by logs on the RPA cloud platform.
  • First, Bot will be developed on the RPA platform, which includes all the steps from RPA technology, and then we run the Bot to the cloud Infrastructure for running the process automatically on cloud engines.
Example 
  • Suppose a real business process scenario, an organization store all its data to a cloud data store service (S3 bucket in AWS), and they want to analyze the data for a specific purpose. Then RPA bot can automate this process of storing data and getting the required data in a file(Excel) on the cloud infrastructure.
Almost 55% of retail work can be automated because 55% of work includes processes that are rule-based and repetitive.Taken From Article, How is RPA changing the Retail and CPG Industry?

What are the Challenges of RPA on Cloud Architecture?

Cloud does not support every process to be automated. So the following are the challenges that can happen while Cloud adopting RPA automation :
  • The cloud architectures are paid, and RPA bot testing on the Cloud can be costly.
  • If the changes occur in the Cloud interface, then the RPA bot should get the update or stop working.

What are the benefits of RPA Cloud Architecture?

Integration of RPA on cloud architecture provides RPA as service to the Cloud, RPA bot running on the Cloud by using cloud services to benefit the organization. RPA, when integrating on the cloud, benefits the cloud user in the following ways.
  • Cost-Effective: If RPA Bot runs the local Machine, the organization will be responsible. Still, if the RPA bot runs on computing engines, then the cloud administrator is responsible for all the backend servers for the machine, and the business process will run as according.
  • Time-Saving: RPA Bot saves time for the AWS business processes as Bot continuously runs the operations and will not ask for the Bot.
  • If the electricity supply is not there on the local machine, the server down, the Bot will stop and did not execute. Still, suppose the Bot will execute on the Cloud Computing Platform. In that case, the Cloud provides HAA (Highly available add-on) that will create a replica of the infrastructure to face such problems.

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Summary

RPA on cloud Architecture is how the RPA bot integrates to cloud architecture and how it performs cloud architecture tasks.RPA can be used as a service to the cloud architectures (Raas). Cloud is a technology where every organization moves to better business and better productivity. Cloud provides services to the organization like to store data, documentation, etc. RPA on cloud architecture could be challenging to implement. When implemented, the organization can benefit on a large scale. Such as cost-saving, time-saving, Increase organization elasticity, and increase the product's productivity.

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dr-jagreet-gill

Dr. Jagreet Kaur Gill

Chief Research Officer and Head of AI and Quantum

Dr. Jagreet Kaur Gill specializing in Generative AI for synthetic data, Conversational AI, and Intelligent Document Processing. With a focus on responsible AI frameworks, compliance, and data governance, she drives innovation and transparency in AI implementation

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