Operations | Monitoring | ITSM | DevOps | Cloud

In today's digital age, customer expectations are soaring. Personalized interactions, round-the-clock availability, and efficient resolutions are no longer luxuries but necessities. To thrive in this competitive landscape, businesses are turning to AI-powered customer service platforms that leverage the power of artificial intelligence to revolutionize customer support.

The use of Internet of Things (IoT) technology is revolutionizing the logistics industry transforming it into an tech savvy sector. By incorporating sensors real time data analysis and automation logistics operations are becoming faster, smoother and more resilient. This shift, towards IoT in logistics, is reshaping how goods are transported from one place to another enhancing supply chain performance and adaptability.

In the realm of education, the pursuit of effective tools and strategies to enhance learning and development is a constant endeavor. One such approach gaining traction is the implementation of RAG technology, a powerful tool that can help benefit the development and monitoring student progress.

In this article, we'll explore how we developed an Aspire component that spins up an Ollama container and downloads a Large Language Model, ready for use. If you're new to any of these technologies, you can continue reading, otherwise feel free to skip to the technical walkthrough. As a quick bit of background, we recently released an Aspire component that brings a free, lightweight Raygun app into your local development environment to help debug exceptions. We then subsequently enhanced this with AI Error Resolution capabilities which runs entirely on your local machine.