A problem we solve in this market .

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Indsutry potential

  • Network independent devices
  • Share learning without moving data
  • Preserving data privacy
  • with >50x network and cloud reduction
  • resilient to network bottlenecks Iot data dynamics
  • Resulting in better AI performance and robustness

Greater accuracy

x2

Reduction in communication
overhead costs x50

x50

Reduction in wall to wall
learning times

x10

Fixed per hour CPU cost £0.60

£0.60

Fixed OP infrastructure cost £150

£150

Reduction in cloud CPU/GPU
cost x100

x100

AI team overhead saving

x3-4

TCO reduction x10

x10

Use case .

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Problem

Learn to predict machine stoppages with high frequency data from across customers. Customers are IP sensitive and will not share data to the OEM.

Solution

Generate, deploy, and manage Edge AI using privacy preserving Federated Learning Ops with OctaiPipe using an infrastructure that is economically profitable.

Impact

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  • 5% reduction of spoilage events
  • Increase revenue by ~£3.9M per line per year
  • 5x more profitable with octaipipe vs. cloud

FAQs

01

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03

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04

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06

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Tristique et egestas quis ipsum suspendisse. Quisque id diam vel quam elementum. Risus viverra adipiscing at in tellus integer feugiat scelerisque. Purus in massa tempor nec feugiat nisl pretium.