The secret to getting ahead with IoT: three advanced IoT technologies

Miruna Suru

Product marketing at Waylay

The secret to getting ahead with IoT: three advanced IoT technologies

The secret to getting ahead with IoT: three advanced IoT technologies

Miruna Suru

Product marketing at Waylay

As companies move from PoCs (proof-of-concept) to pilots and into full production roll-outs, companies test and validate many different technologies in the IoT stack and learn valuable lessons along the way:

  • manual processes should be eliminated wherever possible
  • extracting real business value from raw IoT data is hard
  • integrations and workflows are cumbersome to build and maintain between platforms, backends, and enterprise applications
  • building applications and services is more difficult than anticipated

Often times, a technology choice that seemed good enough in the early stages of an IoT project no longer stands the test of scale and complexity growth in production environments. Other times, as device data starts to stream, companies realise that only a small fraction of it is actually used, raising difficult questions with regards to the actual business value of the IoT solution.

In order to make better use of IoT data, to ensure that all stakeholders gain access to it and to abstract away IoT system complexities, enterprises are choosing to rely on three technologies – automation, orchestration, and intelligent APIs – to ensure efficient, secure and cost-effective IoT deployment and ongoing solution management.

In this recently published whitepaper, Leading IoT analyst firm MachNation discusses these three technologies and presents two use cases describing how they aid in development, deployment, and operation of typical enterprise-grade IoT solutions.

20%

avg.
Cost saving

36%

AVG. reduction in
travel distance and time

11%

AVG. increase in
capacity

1.3

AVG. additional
appointments per shift

99.5%

Improved
SLA adherence

20- 30%

Improvement in
First-time fix-rate

See the video below to see the combination of Waylay and FLS VISITOUR in action:

What’s next?

Autonomous service operations is getting supercharged by the advent of smart synthetic software agents, powered by Large Language Models (LLMs). These synthetic agents will assist human service agents to increase capacity and reduce tedious manual work, like root cause analysis of asset performance issues, updating work plans to deal with impending asset shut downs, etc. 

LLM technologies have matured enough to couple automated asset health monitoring with autonomous field job scheduling to improve asset uptime and Service Level Agreement adherence. Waylay’s analytics and orchestration platform can serve various agentic LLM applications for autonomous service operations that leverages the FLS VISITOUR scheduling engine to optimize the field force load and reduce wasted travel hours. The result is  faster preventive asset maintenance activities, less human error during scheduling and an overall better end customer experience.

Want to know more? Please get in touch with us here

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