On September 23, I ran the third workshop in the AI Lab series at University of Borås. This time we tackled the gap between experimentation and production: the “throw it over the fence” problem that kills ML projects. This post shows how to bridge that gap with MLOps practices and tools.

On September 9, I ran the second workshop in the AI Lab series at University of Borås. This time we tackled a common business problem that you run into all the time when starting an AI project: You have the data, but it is unlabeled. This post shows how to handle that challenge with few-shot learning.

On August 26, I ran the first of three workshops at the University of Borås. The objective was to introduce 25 developers to machine learning and have them build a bunch of models while avoiding common pitfalls.

What gives you a greater competitive advantage than generative AI, language models, RAG & agents?

We leverage our expertise in AI and data engineering to make your business more efficient. Whether you already have a data team or are just starting out, we provide the resources you need to succeed with your data projects.