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Industry

Manufacturing & Logistics

From maintenance manuals to shipping exceptions, manufacturing and logistics run on documents and sensor data. We build AI that works at the edge and in the data center.

ITAR / EARISO 27001IEC 62443Data residency
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The challenge

Why AI stalls in Manufacturing & Logistics

Operational knowledge is scattered across manuals, maintenance logs, sensor systems and the memory of experienced staff. Plants often have limited connectivity, and export-controlled designs cannot leave approved environments.

Our deployment pattern

How we make it work

We run compact models at the edge for plant-floor use and larger models in the central data center, connected to CMMS, MES and document systems. Vision models run on edge GPUs close to the line. Everything works with intermittent connectivity and within ITAR or EAR boundaries where required.

Use cases

Where private AI pays off first

Use case

Maintenance copilot

Technicians ask questions of manuals, work orders and sensor history.

Use case

Quality inspection

Vision models flag defects on the line.

Use case

Exception handling

Triage shipping and supplier exceptions automatically.

Use case

Demand planning

Combine forecasts with unstructured market signals.

Use case

Supplier document processing

Extract data from certificates, invoices and shipping documents.

Use case

Safety procedure assistant

Answer questions from current safety and SOP documentation.

Compliance

Frameworks we design around

We don't certify you, but we build and document systems so your compliance team can map them to the rules you answer to. Every deployment ships with an evidence pack covering data flows, access control, logging, model change management and incident response.

ITAR / EARISO 27001IEC 62443Data residency
FAQ

Common questions

Can models run without internet?

Yes. Edge deployments are designed to run fully offline and sync when connected.

Do you support OT networks?

We work with your OT and security teams to deploy within IEC 62443 zone and conduit designs.

Next step

Find out what private AI would cost you.

A 45-minute call with an engineer, not a sales script. You'll leave with a rough architecture, a cost range and the next three steps.