Smart Reasoning for IoT----waylay.io

Customer care is an essential ingredient in the customer experience strategy of any service provider. Customer care consists of self-care, assisted care and predictive care.

Both self-care and assisted care are reactive in nature. In contrast, predictive care proactively identifies and diagnoses problems, and potentially even tries to resolve them before customers call to the helpdesk

The challenge for service providers and their suppliers is to embrace a new generation of technology that can make both self-care and assisted care more efficient and effective. Big data, machine learning and the API-economy are technologies that are not used to their full extent in the context of care, but which can lead to dramatic performance improvements.

Predictive care is typically still underdeveloped, the challenge for service providers is to use the data embedded in operational systems for customer care purposes in a proactive way.

Current self-care and assisted care solutions are based on classic workflow technology and act according to a static sequence of steps, where customers are asked a fixed set of questions for problem resolution. Updating the workflows over time is hard, as often large parts of the workflow need to be rewritten from scratch. Workflows also tend to grow big fast, which make them harder to maintain.


The main focus today is still on reactive care, i.e. swiftly resolving issues once they have occurred. While a good approach, predictive care can take this to the next level, by avoiding people call the helpdesk in the first place

waylay’s platform is able to dynamically reorder the list of questions and measurements in order to get to problem resolution in the fastest possible way. It accomplishes this by exploiting historical data as well as real-time recomputing the optimal order of steps based on real-time answers and measurements. The waylay platform is continuously self-optimizing and learning, without requiring any code change!

waylay’s technology is also a platform for proactive customer care as it allows periodic collection of data from a variety of cross-departemental and even external systems, reason on those data and act on the outcome of the reasoning process.

Evolving from reactive to predictive maintenance

Predictive maintenance can resolve issues related to fixed maintenance schedules or pure reactive maintenance. Predictive maintenance allows to detect problems upfront or as soon as they occur and resolve problems proactively. Predictive maintenance relies on data analysis to optimize maintenance schedules, avoid downtimes and optimize services costs.