Artificial Intelligence

The technology that allows companies to configure computer software called “robots” that automates human activities is Robotic Process Automation (RPA). RPA software automates rules-based and repetitive processes that are performed by experts while sitting in front of computers.

Software robots can open email attachments, complete e-forms, records, and perform several other tasks that simulate human action. Robots can act as a virtual workforce while assisting with front-office staff—for example, helping call center agents during client interactions and automatically taking close call notes.

Natural Language Processing (NLP) is “the ability of machines to understand and interpret human language the way it is written or spoken.” The objective of NLP is to make computers/machines as intelligent as human beings in understanding language. The ultimate goal of NLP is to fill the gap between how the people communicate (natural language) and what the computer understands (machine language). There are three different levels of linguistic analysis done before performing NLP-

Customer Experience (CX) focuses on the general experience a customer has with a company. It involves several interactions a person has with your brand. The main objective is to increase customer satisfaction, loyalty, and advocacy. It includes your customer’s overall experience, continued usage, and recommendation to others. Customer Experience means how customers perceive their interactions with your company. Good CX gives a user/customer the ability to –

AI can be used to study complex and large datasets to derive patterns. It has reshaped the decision-making process in companies and has found its use case in several industries such as healthcare, manufacturing, retail, supply chain, finance, etc.

As an AI solution provider, we collaborate with companies to build models to help them discover new patterns within their data. We use TensorFlow to create AI models and use microservices offered by prominent cloud service providers such as Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle Cloud to quickly and easily train, and deploy these models at any scale.