Insights on Leveraging GenAI for Speed and Scale: A Discussion with Mad Engine and Columbus

Insights on Leveraging GenAI for Speed and Scale: A Discussion with Mad Engine and Columbus

Exploring AI Developments in Business: Insights from the AI Agent & Copilot Podcast

Welcome to an exploration of the AI Agent & Copilot Podcast, where we dive into the latest trends and developments in AI, particularly from Microsoft and its partners. This article summarizes a recent episode where hosts discussed engaging topics related to AI applications in business, featuring key speakers from the upcoming AI Agent & Copilot Summit.

Understanding the Participants

Mad Engine: A Fresh Look at E-commerce and Data Management

Mad Engine is a dynamic company in the graphic T-shirt retail and print-on-demand market, primarily focused on e-commerce. Representative Tokuno emphasizes her role in managing business data, leveraging systems like ERP and Dynamics to optimize operations.

Columbus: A Leader in Consultancy and AI Solutions

Columbus, a global consultancy with its headquarters in Copenhagen, Denmark, has extensive experience with Dynamics products and data management. Their firm operates around the clock, featuring development centers in multiple countries to support their global clientele.

The GenAI Project at Mad Engine

Accelerating Business Processes

Tokuno highlights a collaborative project between Mad Engine and Columbus that leverages Generative AI (GenAI). This innovative project was initiated due to the company’s interaction with over 60 unique customers. Each customer needed distinct upload sheets – essentially, Excel files that facilitate order processing. With varying needs and a market that demands quick turnaround times, the reliance on manual data entry became a bottleneck.

To tackle this challenge, Columbus employed AI technology to automate data entry, successfully filling out an impressive 85% of the required information. This automation led to a remarkable accuracy rate of 96%, allowing Mad Engine to significantly ramp up their design production from approximately 300 to nearly 2,000 designs.

Key Objectives and Takeaways from the AI Agent & Copilot Summit

A Focused Approach to AI Integration

Simms, another speaker at the podcast, outlines the primary goals for the upcoming AI Agent & Copilot Summit, scheduled for March 17-19 in San Diego, California. He emphasizes the necessity of developing a Proof of Concept (POC) to reduce risks and changes during project implementation. By integrating diverse technologies within the AI landscape, such as data engineering and prompt engineering, presenters aim to craft customized solutions suitable for Mad Engine’s specific operational demands.

Insights from Mad Engine’s Experience

Tokuno shares valuable insights derived from their journey working with Columbus, underlining the significance of the POC process. This collaboration revealed crucial aspects often overlooked in traditional business approaches, especially ones involving human dynamics. The project’s focus transitioned from merely achieving financial savings to enhancing speed to market – a crucial factor in the fast-paced e-commerce landscape.

Through this partnership, Columbus enabled Mad Engine to recognize the potential of GenAI, prompting a reassessment of their business strategies and objectives.

The Importance of AI in Modern Business

AI plays a pivotal role in today’s business environment, particularly for mid-market and enterprise companies. The AI Agent & Copilot Summit serves as a platform to define the opportunities and impacts AI can bring to business operations, exploring how tools like Microsoft Copilot can transform customer interactions and efficiencies.


This article illustrates the discussions from the latest AI Agent & Copilot Podcast episode, shedding light on how companies like Mad Engine and Columbus are harnessing AI to drive innovation and improve business processes. Their experiences showcase the transformative potential of AI in enhancing operational efficiencies and adapting to market demands.

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