At DiUS, we always look for challenges in automation and testing when building solutions for our clients. Automated deployment and testing are key to any successful development process, and are particularly important for reproducible machine learning experiments. In this blog post I will explore how Amazon Personalize is helping to accelerate the machine learning lifecycle and where we think the challenges are for the important topic of automated deployment.
Rapid changes in customer behaviour requires businesses to adapt at an ever increasing pace. The recent changes to our work and personal life has forced entire nations to work remotely and do all non essential shopping online. With every challenge in business there is opportunity on the other side.
In Part 1 of our blog, we set out to answer a number of questions around scaling up development of Amazon Connect. In short, we found two things. This post continues the journey as we try to answer these questions: Is there some way to "pass through" the conversation from Connect to another NLU solution like Rasa? And Is there really no way to automate deployments of our flow logic?
If you work in the call centre space, you’ve probably heard of Amazon’s cloud contact centre offering Amazon Connect. And if you’re based in Australia you might also have heard that Amazon made Connect available here in early 2017. A diverse range of companies including NAB, Square and Subway (to name a few) have already started migrating parts of their call centre operations to Amazon Connect.
