Edge AI & IIoT


Edge AI & IIoT

Run AI where the data is. Edge deployment puts inference next to the machine for real-time action — millisecond decisions, offline resilience and secure edge-to-cloud — ideal for fast lines and remote sites with limited connectivity.

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Edge inference
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Offline-capable
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Autonomous

How we apply it

We deploy models to industrial edge gateways and PLCs, connect them via OPC UA and MQTT, and stream only what matters to the cloud. Decisions happen locally and instantly; the cloud handles fleet monitoring, dashboards and retraining.

  • Edge inference on gateways and IPCs
  • IIoT connectivity (OPC UA, MQTT, REST)
  • Real-time control actions and reject
  • Store-and-forward for low connectivity
  • Secure, managed edge-to-cloud
  • Fleet monitoring and OTA model updates

Representative projects

Anonymized project profiles across industries. No client names or sensitive data are disclosed.

Manufacturing
High-speed line — real-time reject

A line ran too fast for cloud round-trips; defects had to be rejected inline.

Result: millisecond on-edge decisions with no line slowdown.

Mining
Remote site — intermittent connectivity

Predictive models had to keep running where the network dropped for hours.

Result: fully autonomous edge operation with store-and-forward sync.

Automotive
Multi-plant — fleet of edge devices

Models needed consistent updates across plants without on-site visits.

Result: centrally monitored fleet with over-the-air model updates.

Capabilities

Edge inferenceIIoT gatewaysOPC UA / MQTTReal-time controlStore-and-forwardSecure edge-to-cloudOTA updates