Data

We are absolutely thrilled to share the riveting experience we had at the training event organized by the Entrepreneurs’ Organization (EO) Paris Chapter. Our CEO, Stephane Monsallier, had the honor of leading a dynamic session on the potential and application of Generative AI for businesses. We would like to extend our sincere gratitude to EO Paris for giving us this opportunity and to Mydral for graciously hosting this event.

On January 11th, Shanghai’s vibrant startup community gathered for a night of learning and networking at the Startup Grind event. Entrepreneurs from all walks of life congregated to learn, share, and engage with one another. The event was marked by an exchange of ideas, insightful conversations, and an atmosphere that was palpable with entrepreneurial spirit.

As the adoption of Generative AI (GenAI) technology rises in large companies, IT managers are facing a unique set of challenges and concerns. Although GenAI holds immense potential to streamline operations and drive innovation, it also introduces new complexities in terms of management, security, and control.

Artificial Intelligence (AI) has become a buzzword in many industries, and it is fast becoming a reality for many knowledge workers. Organizations must understand how to best integrate AI to empower their employees. The knowledge worker is a vital asset in any company, and AI can help empower these workers by providing them with the information they need to make better decisions, faster, and focus their energy on higher value creation tasks.

We developed a methodology to help our clients design critical numbers for all their projects. It has become an essential part of our toolbox to ensure that a project: delivers value, serves a business objective, is judged on objective success criteria. This tool is both a business and project management tool, as it aligns both views and objectives.

Good data is the basis of good decisions in companies. Good data is also necessary to enjoy the benefits of business intelligence and machine learning. It is then surprising how much corporates spend on shiny technology versus producing good data. High-quality data can be an asset to companies that know how to use them.