Analytics and machine learning apps that run directly on your edge nodes, deployed from the EmberNET App Store in minutes, not months.
Deploy computer vision models directly on your edge nodes to inspect parts, surfaces, and assemblies in real time at line speed, without sending video to the cloud. Catch defects, dimensional deviations, and labeling errors before they leave the station.
Vision inference runs locally on the EmberNET node, keeping cycle times tight and your production imagery on-premises.
Read the white paper : Vision Inspection at the EdgeVision-language-action (VLA) models let robots understand their environment and act on natural-language instructions instead of just following hard-coded paths. Run VLA inference at the edge on EmberNET nodes, so your AMRs and robotic arms respond in real time without a cloud dependency in the loop.
Low-latency edge compute is the prerequisite for autonomous robotics in production. EmberNET provides the infrastructure layer that makes it viable on the floor.
Read the white paper : Robots That Take InstructionsAI scheduling models that run on-site, not in a cloud your production floor can't wait for. Sequence jobs, balance machine loads, and adapt to real-time constraints like downtime, material shortages, and priority changes, all without a round trip to a remote optimizer.
When the WAN link drops, production doesn't stop. Decisions are made locally, against live shop-floor data.
Read the white paper : Scheduling at the EdgeA conversational AI interface built for maintenance technicians. Ask about equipment history, fault codes, recommended procedures, and parts inventory in plain language, and get answers grounded in your actual asset data, not generic documentation.
It runs on the EmberNET platform, so your maintenance team has access on the floor whether or not there's a cloud connection.
Read the white paper : The Maintenance Assistant That Knows Your PlantTalk to our team about your environment and which AI solutions fit.
