IoT and AI with Edge Computing


Professional IT Services & Technology Consulting

IoT is an essential part of businesses all over the world, and we realize that companies have to manage and deal with this new wave of technology. As a result, IoT became one of buzzword everywhere, however the concept has not yet realized its’ full potential.

Latona is challenging this circumstances via the novel end point solutions utilizing Nvidia and ARM that are embedded with distributed IoT fogs, data stacks, API stacks and scaling clouds (deployed from the center of the cloud).

Core frameworks

Latona's original micro-services core framework

  • Kubernetes on the Edge dedicated to industrial data controlling and micro-services oriented business logic
  • Horizontally scalable with Nvidia and ARM based motherboards
  • AI computing vision and ML ready
  • Graphical flow designer with zero programming approach
  • Versatile data stack on the Edge
  • Cloud integration with AWS or Azure IoT Fog services
  • Integrated CI/CD workflow to facilitate new services development
  • M2M micro-payment service with hyper-ledger blockchain (future release plan)

Need to build fully connected services

Latona not only leads our clients through our services, but also other startups across multiple tech platforms, tech driven consulting firms, and cloudization product providers to connect all the relevant IoT resources to Latona’s Open Source network and its participants.

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Use cases


In factories, the machinery equipment is running very often isolated or is integrated in silos that make difficult to collect and analyze efficiently the data.

In order to improve this workflow, it is necessary to build performant data pipelines that will ingest those data and organize them in a comprehensive format.

Then thanks to the next generation of smart edge computing we are able to process this data close to the process to provide near real-time analytics.



There are many processes that are not yet fully optimized and many solutions have been developed like robotics, RFID based analytic solutions to address those problems.

However, we are still lacking real time analytics that fully give us a clear picture of the processes status as there is an important latency with the current solutions relying on Cloud environment with limited edge processing.

Our solution is filling this gap by giving more power on the edge to perform advance computational analytics that is necessary to have a more accurate picture about the business processes and fully optimize them.


We are currently working with industrial drone makers to build new services for constrained environment where human intervention is risky or impossible.

Pure Cloud solutions are inadequate and would bring too much risk for the operation, therefore smart edge solutions are the right choice and would be an enabler to bring advanced computational capabilities like computing vision on site with real time feedback on the monitored assets.

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