Zeblok packages and orchestrates the installation of tuned microservices onto remote networks of edge and IoT devices so they can be API invoked for local AI inferences and insights.
The hard problem of intelligent IoT has long been the non-standard nature of devices, and the variety of platforms and hardware requirements that must be vertically integrated to make application logic and decisioning happen as smoothly as we might have expected from watching our favorite sci-fi shows where physical surroundings take on responsive behaviors.
Zeblok’s Ai-MicroCloud installs a lean infrastructure-as-code footprint onto devices that load in inference apps and custom AI models, running them even on commodity hardware using fractional amounts of shared CPU and memory capacity.
Optimizing overhead requirements allows their platform to run marketplace apps with ‘timeshare’ multitenancy on a wider array of networks of smart cameras or kiosks, where multiple workflows and algorithms can gather live data and respond to local stimuli.
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