Burnie Group’s intelligent automation program can help your organization to reduce costs, increase productivity, improve employee engagement and streamline business processes.
What is intelligent automation (IA)?
Intelligent automation (IA) is the intersection of artificial intelligence (AI), digitization (OCR/ICR/HCR) and robotic process automation (RPA). Where RPA addresses manual, structured and repetitive tasks that can be mimicked and automated by a bot, intelligent automation introduces reason and cognition to digitize and structure inputs, to make judgement-based decisions without human intervention. Essentially, IA can take immense amounts of data and process it into a meaningful output, which can then be used to automate processes.
How is IA different from RPA?
RPA looks at manual, structured, and repetitive tasks that a bot can mimic and automate. IA can automate standard tasks and apply cognitive intelligence (machine learning, NLP, Neural Networks) to tasks requiring decision-making without any manual intervention. RPA is tactical, whereas IA is more strategic as it is central to the core business vision and roadmap.
Burnie Group’s intelligent automation consulting and implementation capabilities
Natural Language Processing (NLP): Natural language processing (NLP) is a computer’s ability to understand, interpret, and generate written and spoken language. Read more here.
Machine Vision: Machine vision a combination of hardware and AI-based software that guides devices to execute their tasks based on the capture and processing of images. Read more here.
Intelligent Virtual Agent (IVA): An intelligent virtual agent is a type of chatbot that can interpret voice and text in free form (chat) to respond with predefined standard answers. These chatbots can continuously learn and build vocabulary to interpret the unstructured information directed to them. IVAs are commonly displayed on website home pages to interact with a user.
Machine Learning: Machine learning is a field of artificial intelligence that enables computers to consume large data sets, discover patterns and learn to perform specific tasks without being explicitly programmed to perform those tasks. Read more here.
Deep Learning: Deep learning is a subfield of machine learning that uses algorithms inspired by the biological brain’s structure called artificial neural networks. Deep learning enables a computer to learn without supervision by drawing from data that is unstructured and unlabeled. Read more here.