Automation Anywhere has significantly transformed its platform. Previously, tasks were created and managed locally through the control room panel. However, with the introduction of cloud technology, users can now build and deploy tasks directly in the cloud. By installing a bot agent runner on their systems, tasks can be executed automatically. Furthermore, the platform now integrates with Git and Azure repositories, enabling version control and collaborative development. This means multiple users can work on a single project simultaneously, enhancing efficiency and promoting agile methodologies. Additionally, the platform offers automated code review capabilities, allowing users to track changes and identify contributors. The control room manager also receives email notifications for any modifications made. This transition to the cloud has been a gradual process, spanning two to three years, and has significantly improved the platform's accessibility and functionality.
Automation Anywhere has a two to three-month learning curve.
Integrating Copilot into our system is straightforward. From a chatbot perspective, we can use it for tasks like sending emails or completing daily assignments. By utilizing Automation Anywhere, we can build an agent that functions as a Copilot, automating tasks for us. Copilot is also integrated with machine learning models, providing prompts and responses that can be modified as needed. Its user-friendly interface and ability to integrate with existing applications make it a valuable tool for streamlining daily tasks and improving efficiency.
Copilot has helped to improve our productivity by up to 30 percent.
With the use of Automation Anywhere, the organization has seen improved efficiency, particularly with the introduction of IQ Bot and Metabot for tasks such as extracting data from invoices and purchase orders. The combination of RPA with AI and cloud solutions has considerably transformed our processes, allowing for intelligent document processing and seamless system integration, thus streamlining operations.
I use a variety of AI technologies for our research and development, including generative AI, custom bit models, GPT-4, and LaMDA. We've also built our own product for GPT-4 called Thor, which utilizes intelligent document processing to extract data from contracts, purchase orders, invoices, and receipts. This data is then integrated with our machine-learning models and downstream systems. Our focus is on transforming our processes using RPA, AI, and cloud technologies, migrating existing systems to the cloud and enhancing them with AI and ML capabilities.
I have integrated Automation Anywhere with numerous applications, including Salesforce, ServiceNow, ITSM, SAP including S4/HANA and Fusion, Oracle including Oracle Fusion, Java Technologies, .NET Platform, Maple's Web Platform, various databases including QLS with dual database configurations, and Power Platform. I am also familiar with backend systems like Data Lake.
I enjoy using applications and API integration tools to efficiently connect systems. Our organization favours API automation, so we developed an ML-based automation product. We prioritize API integration for all applications, leveraging our back-end team and custom APIs for seamless connectivity. While UI automation can be time-consuming, API integration, especially with back-end services, is significantly faster. Our strategy involves collaborating with IT business partners to prioritize API development.
Automation Anywhere helps us save at least 85 percent of our costs.