Technology has accelerated changes toward information-based healthcare delivery and management. Today’s multi-disciplinary approach to delivering better healthcare outcomes coupled with advanced imaging and genetic-based customized treatment models depend on AI/ML driven information systems. At Robin.io, we believe machine learning is the life-saving technology that will transform healthcare. AI/ML challenges the traditional, reactive approach to healthcare.

Coca-Cola is one of the most recognizable brands on the planet. That’s because wherever it’s produced, the quality, product, and design are the same. When three Coca-Cola companies merged in 2016 to create Coca-Cola European Partners, operational differences became apparent. The company needed a way to standardize platforms and processes across 13 Western European countries and 50 bottling plants. We had three systems in place, three ways of working, and multiple languages.

Telecom companies monitor their network using a variety of monitoring tools. There are separate fault management and performance management platforms for different areas of the network (core, RAN, etc.), and infrastructure is monitored separately. Although these solutions monitor network functions and logic – something that would seem to make sense — in practice this strategy fails to produce accurate and effective monitoring or reduce time to detection of service experience issues.

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week we explore the rising scope of location intelligence in improving the overall customer experience.

Conversational AI chatbots are a new vector of artificial intelligence use case that makes the user experience satisfactory, providing immediate response. This technology enables users to converse with applications through various means, such as via text, voice, touch, or gesture, which are closely the same as humans. Users find it much more impressive as they can communicate with their vocabulary and terminologies.

Running an Artificial Intelligence (AI) infrastructure on premise has major challenges like high capex and requires internal expertise. It can provide a lot of benefits for organisations that want to establish an AI strategy. The solution outlined in this post illustrates the power and the utility of the universal Operator Lifecycle Manager (OLM) using Juju, a universal OLM, to create and manage on premise AI infrastructure.

This article was previously published by Raconteur. Unmanageable workloads often have a knock-on effect on the customer experience (CX), and businesses can no longer afford to get this wrong. The expectation of an always-on experience and increasingly saturated markets can mean a poor experience will send customers elsewhere. And yet, many businesses are struggling to deliver the great customer experience that is demanded.

Artificial Intelligence is in the news a lot, and it’s hyped as a cure for all ills in the same breath it’s suspected of spelling doom for us all. What’s the truth behind all the noise? What does artificial intelligence do, seeing as it is simply everywhere. The truth of the matter is that whatever the would-be prophets say, artificial intelligence and machine learning is here, now, and has applications to your day-to-day.

With build-or-buy decisions, it often comes down to an all-in-one platform or a mixture of best-of-breed technologies. With open-source technology companies can actually get the best of everything. So, why not roll your own platform based on top-notch technologies? The real question is whether enterprises can afford to. Open-source software is free to use, but teams have to invest quite a bit in selecting, introducing, using, and maintaining these technologies.