RPA With SAP Intelligent Robotic Process Automation 

iRPA is designed to work seamlessly with various types of applications. It supports native integration with traditional desktop applications such as Microsoft Office, browser-based SaaS platforms, headless or microservices-based applications through APIs, and applications running in virtualized environments. This versatility reduces the need for desktop maintenance and increases automation reach across business systems.

Instead of relying on fragile screen scraping techniques, iRPA leverages the HTML and XML DOM to interact with screen elements programmatically. This method ensures that automation remains stable and resilient, even when there are frequent changes in the user interface. As a result, bots can continue functioning with minimal rework or maintenance.

iRPA enables direct communication with enterprise systems via application programming interfaces (APIs). This approach significantly enhances bot performance, reduces latency, and ensures long-term compatibility with systems undergoing frequent upgrades. By bypassing the UI layer, iRPA makes automation more reliable and less prone to user interface changes.

With the help of machine learning and AI, iRPA can intelligently process both structured and unstructured data. This includes capabilities such as image recognition, text classification, and natural language interpretation. iRPA can extract meaningful information from various sources including emails, chat conversations, documents, and web content.

iRPA supports both attended and unattended automation, making it flexible for different operational contexts. Attended bots work alongside users, while unattended bots operate independently. Additionally, iRPA allows users to interact with automation via natural language and speech-to-text interfaces, enabling seamless control from any device without needing to navigate complex user interfaces.

iRPA integrates with platforms like SAP Conversational AI to deliver intelligent, chatbot-based user experiences. These bots use natural language processing (NLP) and machine learning to understand user inputs, respond contextually, and continuously improve through interaction history. This creates a more intuitive and human-like automation experience.

iRPA incorporates cognitive automation features powered by machine learning and deep learning. These capabilities enable bots to learn from data over time, adapt to system changes such as altered data formats or unexpected UI modifications, and identify more efficient automation paths. This self-learning ability leads to greater agility and long-term efficiency.