Sovereign AI Infrastructure
for Modern Manufacturing
built for Your Data, Tuned for Your Operations
Pre-built LLMs for patent analysis, shop floor operations, and predictive maintenance fine-tuned on your schematics and sensor data, deployed inside your network, operated by us.
The Challenge
Why generic AI falls short in Manufacturing
Downtime is measured in euros per minute
When a line stops, a generic model can't read your specific PLC fault codes or decades of maintenance logs fast enough to matter.
Process data is your moat
Tolerances, recipes, and process parameters are trade secrets. Pushing them to a public API is an uncontrolled disclosure.
The floor is offline-first
Plants run on segmented OT networks with intermittent connectivity. A round-trip to a SaaS endpoint isn't a dependency you can take.
Generic models don’t speak your domain
Foundation models miss the specialized vocabulary of your equipment, defect classes, and engineering standards.
How Numid Helps
Sovereign AI, built for Manufacturing
Models finetuned on your manuals and logs
A domain copilot trained on your equipment documentation, work orders, and historical fault data — so answers are specific to your plant.
Deployed next to the line
Runs inside your VPC or on an on-premise cluster near the floor — low latency and tolerant of patchy connectivity.
Process IP never leaves
Inference stays inside your perimeter, with audit logs written to your own storage. Full sovereignty by design.
Predictable cost across every shift
Fixed infrastructure instead of per-token billing that balloons when every operator and line is querying at once.
Use Cases
Where it pays off
Downtime & fault-code triage
Operators describe a fault in plain language and get the likely cause, the relevant manual section, and the next step — in seconds.
Maintenance & SOP copilot
Surface the right procedure, torque spec, or safety step from thousands of pages of documentation, grounded in your own sources.
Quality & defect analysis
Cluster defect reports, correlate them with process parameters, and capture the knowledge of retiring experts before it walks out the door.
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