Intelligent Process Automation

Robotic Process Automation Robotic process automation is a form of business process automation technology based on metaphorical software robots or artificial intelligence digital workers.RPA tools have strong technical similarities to graphical user interface testing tools. These tools also automate interactions with the GUI and often do so by repeating a set of demonstration actions performed by a user. RPA tools differ from such systems that allow data to be handled in and between multiple applications, for instance, receiving an email containing an invoice, extracting the data, and then typing that into a bookkeeping system.It is sometimes referred to as software robotics. RPA, among other technological trends, is expected to drive a new wave of productivity and efficiency gains in the global labour market. Although not directly attributable to RPA alone.

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. The term AI may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.

Machine Learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Deep Learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. It is also known as deep neural learning or deep neural network.

Conversational AI is the set of technologies behind automated messaging and speech-enabled applications that offer human-like interactions between computers and humans. Applied Conversational AI requires both science and art to create successful applications that incorporate context, personalization, and relevance within the human to computer interaction. A chatbot is a computer program that simulates human conversation through voice commands or text chats or both. Chatbot, short for chatterbot, is an AI feature that can be embedded and used through any major messaging applications.

Sales Intelligence refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of information to help salespeople find, monitor, and understand data that provides insights into prospects’ and existing clients’ in daily business. The data used in SI solutions are based on either internal data, behavioral data, or open data. Companies use sales intelligence software to improve the quality and quantity of sales leads by using data to find new opportunities and provide salespeople with the information they need to take advantage of them,

Predictive Analysis encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Predictive analytics is used in actuarial science, marketing, financial services, insurance, telecommunications, retail, travel, mobility, healthcare, and other fields. One of the best-known applications is credit scoring, which is used throughout financial services. Scoring models process a customer's credit history, customer data, etc., to rank-order individuals by their likelihood of making future credit payments on time.