Industrial Solutions
Smart factory AI for
Industry 4.0
ROS2-native robotics, predictive maintenance, and edge AI for smart manufacturing. Sub-millisecond control loops, OPC UA integration, and multi-robot fleet coordination — all running at the edge.

Industrial automation
Smart factory AI needs plant-floor context, not abstract product art.
Industrial programs connect robotics, PLC integrations, predictive maintenance, and edge AI into a clear operational architecture.
Plant-floor architecture
Live modelPLC
OPC UA
ROS2
<1ms loops
Edge AI
Fleet orchestration
MES
OPC UA
Signal
OPC UA
Signal
<1ms loops
Signal
Fleet orchestration
Stack
The plant-floor stack, from PLC to MES.
Click any layer to see the components, integrations, and operational guarantees from the robot controller all the way up to the operations workflow.
Industrial stack
6 layersSame image runs on cell controllers, line gateways, and rack-mounted plant servers — DDS Security and TPM 2.0 attestation across all of them.
Production scheduling, quality escalations, predictive-maintenance alert triage, supplier coordination — orchestrated as workflows that bridge MES, ERP, and AI services.
Key Capabilities
Built for smart factories.
Autonomous Robot Fleet
Native Fast-DDS 3.2 integration for ROS2 Jazzy with DDS Security. Multi-robot coordination, path planning, and task allocation across warehouse and production environments.
Predictive Maintenance
AI-powered anomaly detection with emlearn and Apache TVM. Real-time vibration analysis, thermal monitoring, and failure prediction to reduce downtime by up to 70%.
Visual Quality Control
Real-time defect detection with ncnn and MediaPipe. Surface inspection, dimensional analysis, and assembly verification at 100+ parts per minute with 99.9% accuracy.
Platform Integration
NeuralOS for manufacturing.
A real-time Linux kernel purpose-built for factory automation. PREEMPT_RT deterministic scheduling, ROS2 Jazzy with Fast-DDS, and edge AI inference — all in 64MB of RAM.
Deterministic <1ms control loops for safety-critical automation
Connect PLCs, SCADA systems, and factory sensors natively
NPIE v2.0.0 with 12 backends: LiteRT, ONNX Runtime, NCNN, OpenVINO, ExecuTorch, llama.cpp, and QuEST
Trigger, route, and monitor factory workflows across operators and systems
Use Cases
Manufacturing reimagined.
From warehouse logistics to precision assembly, NeuralOS powers the next generation of smart factories.
Sortable comparison across throughput, integration depth, and ROI horizon.
| Use case | Control latency deterministic | Throughput target | MES / PLC integration | Reference hardware | Typical ROI |
|---|---|---|---|---|---|
Warehouse robot fleet AMR / AGV fleet for picking, replenishment, and cross-docking. Centralised dispatcher with NowFlow handles task allocation, charge cycles, and exception handoff. AMR fleetNav2OPC UA | < 1 ms control · < 50 ms dispatch | 1k–10k tasks/day | WMS · OPC UA | Jetson AGX Orin · Cat-1 lift | 8–14 months |
Production-line vision QC Per-station defect detection on the conveyor. Reject decisions in <50 ms, line-rate logging to MES, drift-monitoring alerts trigger NowFlow escalation. Defect CVMES integrationDrift alert | < 50 ms classify | 100–600 parts/min | MES + OPC UA | Jetson Orin Nano + 4K camera | 6–10 months |
Predictive maintenance Vibration + acoustic + thermal models on rotating equipment. NPIE runs the model on the gateway; NowFlow opens a work order and assigns to the right technician. Anomaly detectCMMS hand-offEdge gateway | Periodic | 100s of assets/gateway | CMMS · MQTT 5 | Industrial PC + sensor pack | 10–18 months |
Digital twin Real-time twin of a cell or whole plant — DDS topics from robots and PLCs, simulation runs in parallel, what-if scenarios planned through NowFlow. Fast-DDSWhat-if simOPC UA | Soft real-time | Up to 50 cells / twin | DDS · OPC UA · MES | Industrial PC cluster | 12–24 months |
Visual quality inspection (offline) Air-gapped cells where the model must run on-device. Fully offline NPIE inference, signed audit log to USB stick or local network share. Air-gapAudit logLocal LLM | < 50 ms classify | Per-cell | Local share / USB | Jetson Orin Nano | 4–8 months |
By the Numbers