Real-time AI on the factory floor
Quality inspection, predictive maintenance, robotics, and safety, running right on the machine at line speed. Wendy keeps perception and control local, so production does not wait on the cloud and process data stays in the plant.
Catch defects at line speed with vision models running on the station itself, with no frames shipped to a server and no cloud latency gating throughput.
Vibration, thermal, and acoustic models run directly on the machine, flagging bearing wear, misalignment, and drift long before unplanned downtime.
Perception and control for robot arms, AMRs, and pick-and-place cells run on the cell itself, close to the sensors and actuators, for the low latency a moving line demands.
On-device vision watches for PPE, proximity to moving equipment, and restricted-zone entry, and reacts locally, even fully offline.
Camera feeds, recipes, and process data are competitive secrets. Apps compute locally, so that data can stay inside the plant network, including air-gapped networks.
Stations need no inbound internet access. Manage them over the plant network with mutual TLS and per-device certificates, or through an outbound-only tunnel to Wendy Cloud, now in beta.
Push a new model or app to a station in seconds, or build once and deploy to several stations. OS updates roll back on their own if the new version fails its checks.
Compute throughput, scrap rates, and downtime causes at the edge in real time, and surface the metrics that actually move OEE.
See which stations are online and run device commands remotely, including logs, health, and updates, through Wendy Cloud, now in beta.
Build on the edge compute that survives the floor, from NVIDIA Jetson to Raspberry Pi, mounted on the machine, in the cabinet, or on the line.
Common questions
Direct answers about real-time physical AI for quality inspection, maintenance, robotics, and factory operations.
Manufacturing AI often needs line-speed response for inspection, robotics, worker safety, and predictive maintenance. Running models on the station or machine avoids cloud latency, keeps production data inside the plant, and supports segmented OT networks.
WendyOS can run visual quality inspection, predictive maintenance, robot cell control, safety-zone monitoring, line analytics, and edge gateways on supported hardware such as NVIDIA Jetson and Raspberry Pi class devices.
WendyOS is local-first. Applications, sensor processing, and logs run on the edge device, and teams deploy, update, and debug devices over the plant network with mutual TLS and per-device certificates, so stations can run inside segmented or air-gapped factory networks.
Tell us about your line and your constraints, and we’ll show you inspection, maintenance, and control running right on the machine.