OctaiPipe available to deploy from the Sunlight application library

Deploy, manage and automatically update OctaiPipe Federated AI for IoT solutions and supporting infrastructure across thousands of distributed, edge sites with Sunlight and Lenovo., the thinnest, fastest HyperConverged Infrastructure (HCI) platform built for applications that run at the edge, today announced that OctaiPipe, the trustworthy federated AI learning solution for IoT, is now available to deploy, manage and update from the centralised Sunlight application library (AppLibrary). OctaiPipe demonstrated its products running on Sunlight HyperConverged Edge and Lenovo infrastructure at the Lenovo roadshow in locations across the UK throughout November 2023.

The OctaiPipe mission is to protect the world’s critical infrastructure by putting AI right at the heart of connected devices. The OctaiPipe platform enables the deployment of a new generation of AI-enabled Internet of Things devices (AIoT) that makes critical infrastructure smarter through closed network Federated Learning – ensuring asset health, performance and security while minimising the need for data to move to the cloud. OctaiPipe is use-case agnostic and is delivered ready with apps, tools, and templates for Industry 4.0, energy, manufacturing, utilities, transportation, shipping, smart cities and asset management. Sunlight HyperConverged Edge Computing infrastructure and AppLibrary, running on the Lenovo ThinkEdge and ThinkSystem server range, makes it easy to deploy and scale the OctaiPipe platform across 100s or 1000s of sites from a centralised location.

“OctaiPipe is making the world’s critical infrastructure smarter and safer. Our Federated Learning Operations (FL-Ops) platform enables the deployment of AI to the edge and the management of distributed learning across a network of intelligent devices. Rather than move data from edge devices to the cloud to train AI algorithms – with all the data transfer and storage costs that entails – Federated Learning (FL) instead trains algorithms on-device at the edge with only the results being shared in a decentralised network for continuous, distributed learning. Using FL-Ops also ensures organisations remain compliant with their data privacy and security laws and policies, by leaving the data on the device. An increasingly important aspect given the potential impact and penalties from data and AI regulations such as the EU AI Act.

Having OctaiPipe available in the Sunlight AppLibrary, running on Lenovo ThinkEdge with Sunlight HyperConverged Edge presents a unique opportunity to new and existing Lenovo customers and partners to seamlessly deploy trustworthy edge AI at a global scale using FL-Ops.“ said OctaiPipe Co-founder & CGO, George Hancock.

“With its accelerated and federated AI, OctaiPipe is removing the common IIoT barriers to market while maximising security and privacy. Having OctaiPipe in our AppLibrary means that we can make it easier for them to scale customer deployments and reach new audiences. The Lenovo AI Innovators partner ecosystem is bringing together software providers to offer their customers a full suite of solutions that are relevant to their industry” said Sunlight Founder and CTO, Julian Chesterfield.

OctaiPipe and Sunlight are both members of the Lenovo AI Innovators partner ecosystem, which aims to maximize alignment between hardware engineering and AI software design and performance. By collaborating with the industry’s most innovative AI software companies, the ecosystem helps deploy AI more rapidly, and with increased confidence.

“Our customers realize the advantages of Edge AI, and deploying solutions closer to the point of data capture to run real-time inferencing. That is why we are so excited to be partnering up with Sunlight supports our edge portfolio to significantly improve the efficiency and economics of AI deployments, such as OctaiPipe’s Federated AI for IoT solutions for customers worldwide” said Scott Tease, Vice President and General Manager of HPC and AI, Lenovo Infrastructure Solutions Group.

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