To cut the long story short, RPA means automating operations with a GUI-based software. An agent (either AI-powered or algorithmic) is clicking buttons and filling forms, just like a human employee would do.

In our assessment of automation concepts, RPA is very controversial. From one point of view, it's as far as possible from being an AI-native solution. Basically, the GUI as we know it is something that would be eliminated due to the post-digital transition Read more about the post-digital transition.

On the other hand, in today's businesses, a lot of things rely on GUI-based software systems, and RPA is the best possible approach to include these systems into automated business processes.

So, we don't like the very idea of RPA, but we recommend using it wherever possible. Still, in the background, we are working on an AI that would make RPA redundant one day Learn more about Updait.

The Paradox of RPA: Embracing the Inevitable

RPA is a paradox in the world of automation. While it may seem like a step backward in the age of AI, it is often the most practical solution for integrating legacy systems into modern workflows. The reality is that many businesses still rely heavily on GUI-based software, and RPA provides a bridge to a more automated future.

Why RPA?

• Legacy System Integration: RPA allows you to automate processes that involve legacy systems without APIs, ensuring that these systems can still be part of your automated workflows.
• Quick Implementation: RPA can be implemented relatively quickly, providing immediate benefits and ROI.
• Cost-Effective: Compared to overhauling entire systems, RPA offers a cost-effective way to automate repetitive tasks.

The Future Beyond RPA

While RPA is a valuable tool today, we are actively working on solutions that will make it redundant. Our Updait platform is designed to transform legacy systems into modern, AI-friendly solutions, eliminating the need for RPA in the long run.

Strategic Approach to RPA

We recommend starting RPA-based automation only after building a comprehensive strategy and fully understanding the business process that is being automated. This approach ensures that you are not just automating inefficiencies but truly optimizing your workflows.

Business Process Engineering: The Foundation

Before diving into RPA, it's crucial to reengineer your business processes from the ground up. Our Business Process Engineering services help you analyze, design, and optimize your workflows, ensuring that you are ready for automation.

• Process Analysis and Mapping: Understand your current processes and identify areas for improvement.
• Workflow Automation: Design workflows that are optimized for automation.
• AI-Driven Process Optimization: Leverage AI to continuously improve your processes.

Learn more about Business Process Engineering

Our RPA Services

• RPA Strategy Development: We help you develop a comprehensive RPA strategy that aligns with your business goals.
• RPA Implementation: Our team of experts will implement RPA solutions tailored to your specific needs.
• Continuous Improvement: We provide ongoing support and optimization to ensure your RPA solutions remain effective.

Kor.Gy AI Agent Capabilities

At Kor.Gy, we are pushing the boundaries of RPA with our advanced AI agents. These agents are capable of working in various environments, including GUI, text-GUI, and web interfaces. Our AI agents can:

• Build Processes Through Natural Language Instruction: Our AI agents can understand and execute tasks based on natural language instructions, making it easier to automate complex workflows without extensive programming knowledge.
• Experiment and Research: Our AI agents can experiment in digital environments, research software without human involvement, and evaluate the automation infrastructure. This capability allows them to identify the most efficient ways to automate processes and continuously improve the automation setup.
• Synthesize AI Agents: Our AI agents can synthesize new AI agents, creating a self-improving automation ecosystem. This means that the AI is not only performing repetitive tasks but also generating and optimizing the agents that perform these tasks.

This new level of RPA ensures that automation is not just about executing predefined tasks but also about creating and refining the automation infrastructure itself.

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Tips & Tricks for Robotic Process Automation (RPA)

Tip 0: RPA is only a Temporary Solution

RPA is often a stopgap solution for integrating software that cannot be linked into business processes through APIs. Treat it as a temporary measure until the legacy system without an API can be withdrawn or replaced. RPA should bridge the gap between outdated systems and modern, integrated solutions.

Tip 1: RPA Everywhere

While all described above is true, in the era of AI, outdated software or the absence of an API should not be a showstopper. Whether through APIs or RPA, automation should be pursued relentlessly. RPA can be a powerful tool to automate processes across the board, ensuring that no task is too small or too complex to be automated.

Tip 2: Intelligent Process Discovery and BIg Data

Use AI-driven process discovery tools and rely on Big Data analysis to identify the best candidates for automation. These tools analyze user interactions and workflows to uncover inefficiencies and opportunities for RPA, ensuring you target the most impactful processes. Before investing a cent in RPA, understand that costs of process before and after, and clearly see the expected RoI.

Tip 3: Design for Scalability from the Start

When designing RPA solutions, consider scalability from the very beginning. Use modular and reusable components that can be easily scaled across different departments and processes. This approach ensures that your RPA implementation can grow with your business needs.

Tip 4: Integrate RPA with AI for Enhanced Capabilities

Remember that autonomous agent based RPA should be the standard solution. As a minimal thing, AI would identify failures or non-standard circumstances, what would contribute to safety and reliability of RPA solutions. As a maximum, AI-enabled RPA agents would self-adjust in case of software update or business process modification.

Tip 5: Implement a Bot Governance Framework

Establish a governance framework to manage and monitor your RPA bots. This includes setting up guidelines for bot development, deployment, and maintenance, as well as defining roles and responsibilities. A robust governance framework ensures consistency, compliance, and optimal performance of your RPA bots.

Tip 6: Use RPA for Continuous Improvement

Leverage RPA to continuously monitor and improve your business processes. Implement feedback loops where bots collect data on process performance and identify areas for optimization. This data-driven approach enables ongoing refinement and enhancement of your automated workflows. It's like using mission data to improve future space expeditions.

Tip 7: Prioritize Security and Compliance

Ensure that your RPA implementation adheres to security and compliance standards. Use encryption, access controls, and audit trails to protect sensitive data and maintain regulatory compliance. Regularly review and update your security measures to address emerging threats and vulnerabilities.

Tip 8: Build a Healthy Culture of Automation

Encourage a healthy culture of automation within your organization. Educate employees about the benefits of automation and involve the whole team in identifying automation opportunities. Never treat RPA as a solution to reduce headcount and enable layoffs, and battle these toxic narratives. Automation is eliminating tedious, repetitive and demotivating tasks for any position, freeing up the minds for great things, starting with the greatest: proper life-work balance.

Tip 9: Consider Updait for Legacy Software Overhaul

Remember that AI is simplifying the overhaul of legacy software. Check Updait from Kor.Gy, which provides an economically effective and reliable toolset to replace legacy software solutions with modern, AI-friendly systems that won't need RPA. Always think and count the numbers to understand whether to build RPA or replace legacy software systems.

Tip 10: Minimize AI Usage

AI is a buzzword but remember: the lesser AI, the better. AI is expensive, has significant carbon footprint, not as reliable as formal logic. Relying on good old formal logic and algorithms as much as possible is key for AI project success. A typical success story is: 10% AI, 90% algorithms.

Tip 11: Ensure Manual Backup Operation Mode and Transparency for People

All RPA and AI solutions should support a backup operation mode to be run manually. Additionally, all data processing by such systems must be thoroughly logged, and the design must support easy investigation of issues and retrospective analysis of the results. Even the best robots would break down some moment.

Tip 12: Be Aware of Legal Risks

Remember about legal risks. Ensure that your RPA implementation complies with all relevant laws and regulations to avoid potential legal issues.

Tip 13: Back Up the Data and Use Sandboxes

Back up the data. Ensure simple rollbacks to recover from any issues that may arise during RPA implementation or operation. Robots work fast, and in case they do it wrong, you'll have big problems. Sandboxing robots is a nice containment strategy that would ensure minimal risks.