An Integrated Data Platform is a comprehensive solution that combines various data sources and tools into a single unified system. It enables businesses to efficiently manage, analyze, and derive insights from their data. By integrating different data sets, such as structured and unstructured data, it provides a holistic view for informed decision-making.

A Semantic Model is a representation of data that captures the meaning and relationships between different elements. It provides a structured framework for organizing and understanding data, enabling more effective analysis and interpretation.

Process discovery is a systematic approach to understanding and documenting existing workflows within an organization. It involves analyzing data, interviewing stakeholders, and mapping out activities to identify inefficiencies, bottlenecks, and opportunities for improvement in order to streamline operations and enhance productivity.

Process mining is a data-driven approach that extracts knowledge from event logs to visualize and analyze real-time processes within an organization. It enables identifying inefficiencies, bottlenecks, and opportunities for optimization to enhance operational performance and drive continuous improvement.

Task mining is a data-driven approach that captures user interactions and analyzes them to understand how people perform tasks on their digital devices. It enables organizations to identify inefficiencies, streamline processes, and improve user experiences through actionable insights gained from the analysis of task-level data.

Augmented automation combines artificial intelligence and advanced automation technologies to enhance and optimize business processes. It leverages AI algorithms, robotics, and machine learning to streamline operations, increase efficiency, and improve decision-making, ultimately driving digital transformation and organizational growth.

Applied AI refers to the practical implementation of artificial intelligence technologies in real-world scenarios, where algorithms and machine learning models are used to solve specific problems and enhance decision-making processes across various industries and sectors.

Generative AI is an advanced technology that uses machine learning models, such as Language Models (LLM), to create original content, such as text, images, or even music, by analyzing and learning patterns from existing data. It enables the generation of new and creative outputs based on the learned knowledge.

Data and AI governance refers to the framework and practices that ensure responsible, ethical, and secure management of data and artificial intelligence technologies. It involves creating policies, procedures, and safeguards to protect privacy, mitigate bias, ensure transparency, and promote accountability in data-driven decision-making.