Where CX, AI & automation intersect.

Artificial Intelligence (AI) is fairly useless without Automation.

AI is concerned with creating software capable of mimicking human cognitive functions, and performing complex decision-making tasks such as language understanding, image recognition and problem-solving that can traditionally only be performed by people.

Automation provides the arms and legs; once the AI software has completed its task or made a decision, it is the automation software that is used to carry out the subsequent actions and complete the process.

Intelligent Automation (IA) refers to the integration of technologies like AI, Process Automation (Robotic and Digital – RPA and DPA), and machine learning to automate complex business processes that typically require human involvement. This can include decision making, natural language understanding, and learning from past decisions.

The Intelligent Automation toolkit includes capabilities such as Decision Intelligence, Communications Mining, Intelligent Document Processing, Predictive Analytics and AI-powered Chat and Voice agents.

Robotic Process Automation (RPA) is a form of automation that mimics human actions to perform repetitive tasks, following clearly defined rules. Intelligent Automation, on the other hand, extends far beyond RPA with a suite of AI & ML capabilities, allowing automations to handle more complex tasks that require decision making and adaptability.

Decision Intelligence is a discipline used to improve and automate decision making through AI and continuous feedback. It allows you to codify human expertise and knowledge into a model called a “Knowledge Graph” to replicate human reasoning. It produces decisions that are transparent and explainable.

When combined with automation, it helps organisations to make faster, better decisions, reduce risks, increase efficiency & scale, reduce costs and capitalise on opportunities more effectively.

Comms Mining uses a form of AI known as Natural Language Processing (NLP) and Machine Learning (ML) to extract insights and actionable information from various forms of business communication. This can include emails, chat messages, voice transcripts, CRM entries and other unstructured text-based communications.

It can understand the intent behind a communication, and is particularly valuable for improving customer service, enhancing employee engagement, monitoring brand reputation, and gaining insights into organisational communication patterns. Organisations can then make data-driven decisions, optimise processes, and improve overall efficiency and effectiveness.

Intelligent Document Processing leverages artificial intelligence (AI) and machine learning (ML) to automate the extraction, processing, and analysis of information from documents. IDP goes beyond traditional Optical Character Recognition (OCR) by incorporating advanced AI techniques to handle complex and unstructured data.

The latest approaches include “Contextual Understanding” which provides amazing results. The model will first identify the type of document it is looking at which then gives it context to the sort of information it can expect to find. Then, when digitising the text it goes far beyond simply trying to recognise individual characters; it looks at the individual letters (either typed or handwritten) within the context of a word or sentence to make better predictions and dramatically increase accuracy. GPT models can also leverage vision to understand information presented in an image.

The first step is to understand your process(es). This could be to address a single pain-point, or a organisation-wide review. Once we have documented the “as-is”, we can plan the “to-be”. Then we build and deploy a Pilot for you, usually within 6-8 weeks.