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Top Technologies Powering Intelligent Process Automation and Their Use

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Demand for agility, flexibility, and scalability is driving businesses to embrace Intelligent Process Automation across functions and processes. This foray into integrating IPA to drive intelligent automation is powered by a combination of technologies such as Natural Language Processing, Machine Learning, Computer Vision, Cognitive Automation, Process Mining, Predictive Analytics, and Cloud Computing.

Digital transformation is an imperative all businesses irrespective of size or industry have had to embrace. A vital cog propelling this digital transformation for businesses is automation. Automation today is seen as a must-have capability to stay relevant in the fast-evolving business landscape where customer preferences, demand for agility, and rising costs, are constantly redefining strategies and outlooks. Robotic Process Automation (RPA) and AI-powered Intelligent Process Automation (IPA) have become the frontrunners in this automation journey for businesses across industries. While RPA is mostly rules-based helping with automation efforts across the beginner and intermediate stages of automation, IPA powered by artificial intelligence is used for advanced automation of processes significantly reducing dependence on human intervention. The scope and use of IPA have been on the rise across industries with the penetration of AI opening up uncharted possibilities. This blog lines out the contemporary technologies that are propelling the march of IPA into prominence and their use.

Natural Language Processing (NLP):

Natural Language Processing is a branch of AI within computer science that enables communication between man and machines. It enables machines to understand and interpret human language allowing for the intelligent process automation of tasks that involve unstructured data such as processing emails, customer inquiries, or analyzing text documents. NLP is majorly used in conversational bots, virtual assistants, and automated email routing systems.

Machine Learning (ML):

Machine Learning is another branch of artificial intelligence that has seen a significant rise across industries and domains. Driven by algorithms, machine learning enables machines to learn from available data. ML is used in IPA to analyze large datasets, deliver predictive and prescriptive insights, and optimize processes. Machine learning can be used to automate processes such as document classification, customer behavior prediction, optimizing inventory management, and other similar processes.

Computer Vision:

Much like NLP which helps machines understand human language by way of text and numerals, Computer Vision enables machines to understand and interpret visual information from images and videos. It is widely used to automate tasks related to image recognition, object detection, facial recognition, and visual quality inspection and is applied intelligently to automate processes such as invoice processing, quality control, and visual data analysis.

Cognitive Automation:

Cognitive Automation is a combination of technologies such as ML, NLP, and Computer Vision layered with advanced reasoning capabilities. It enables machines to closely mimic human understanding and comprehension, helping machines make decisions in complex situations. Cognitive Automation is used in IPA to oversee tasks that require higher-level thinking, such as fraud detection, risk assessment, and complex data analysis.

Process Mining:

Process mining as a technology enables businesses to model, analyze, and optimize processes. Process mining as the term infers analyzes event logs and data from IT systems to provide insights into processes and their efficacy. It not just identifies bottlenecks, and suggests process improvements, it also plays a crucial role in identifying automation opportunities and optimizing processes for IPA implementation.

Predictive Analytics:

Built on the foundation of ML, Predictive Analytics uses historical data, and statistical techniques to make predictions about future outcomes. Predictive analytics is key in today’s rapidly evolving business environment as it helps forecast demand, predict customer behavior, or optimize resource allocation. It ably assists in the intelligent automation of decision-making processes and improving operational efficiency.

Cloud Computing:

Cloud computing has become the de facto technology for businesses looking for scalable and flexible infrastructure. It is the same for IPA solutions as it offers computing power, storage, and services on-demand, allowing organizations to quickly scale their automation initiatives. It also provides pre-built AI and ML capabilities, making it easier for organizations to initiate or upgrade their IPA solutions.

Embrace the future with Intelligent Process Automation

The world is evolving at dizzying speeds demanding businesses to keep up with the pace or fall behind. Businesses on the other hand are grappling with unforeseen challenges such as pandemics, labor shortages, sudden spikes in demand, and more. The pace of change in most instances requires an urgent remedy to address the need for managing scale against volatile demand, operational resiliency to face unforeseen events, handling exceptions without human intervention, maintaining operational quality across functions, and deriving maximum value out of all automation efforts. Intelligent Process Automation fulfills this need by using available technologies to create customized automation solutions to make processes agile, consistent, and precise helping you stay ahead of the curve.

Innover’s Intelligent Process Automation (IPA) solutions can be your perfect ally in facing unforeseen challenges and get you up to speed irrespective of your current automation maturity. Our automation experts combine ready-to-use bots, AI models, and robust frameworks, along with a variety of technologies ranging from OCR, ICR, NLP/NLU/NLG, Computer Vision, Deep Learning, Neural Networks, and more to create customized automation solutions that are tactically perfect for your current needs and are strategically primed for the future.

  • Innover Team  |  July 20, 2023   |  

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