Custom AI Development for Manufacturing

Manufacturing data lives on the shop floor, in PLCs, historians, MES, and quality systems, and most of it never reaches a model that could act on it. Custom AI here has to respect the OT/IT boundary, hold to ISO quality and safety requirements, and run reliably where downtime is measured in lost production. We build copilots and domain models on your sensor, maintenance, and supply chain data, deployed in your environment so operational data stays inside your perimeter. The systems predict failures, catch defects, and surface answers for engineers and operators, engineered for the latency and reliability the line demands. This is AI that earns its place next to the equipment.

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How we deliver it

Custom AI Development, built for manufacturing

We connect to your historians, MES, and quality systems across the OT/IT boundary safely, so models learn from real shop-floor data without exposing control systems.

We build domain models on your sensor and maintenance history to predict failures and flag defects, tuned to your equipment and product, not a generic benchmark.

We deploy at the edge or in your cloud for the latency and reliability the line needs, with operational data kept inside your perimeter.

We harden with evals on your historical events and ISO-aligned documentation, then hand over models and code your engineers own.

Where it pays off in manufacturing

Predictive maintenance

Predict equipment failures from sensor and maintenance data so teams intervene before unplanned downtime, scheduled around production.

Visual defect detection

Catch defects on the line in real time from imaging, flagging issues for operators before they ship and feeding quality records.

Maintenance copilot

Answer technician questions from manuals, work orders, and history, so the right fix and parts surface at the machine.

Supply chain assistant

Forecast demand and flag supply risk from your ERP and supplier data, so planners act on signals early.

Manufacturing clients typically cut unplanned downtime and defect escapes meaningfully, turning shop-floor data that was sitting idle into fewer line stoppages and higher OEE.

Manufacturing AI, answered

We integrate through historians, MES, and read paths that respect the OT/IT separation, so models learn from operational data without reaching into control systems. Deployments are designed to fail safe and align with your ISO quality and safety requirements, and operational data stays inside your perimeter.

Yes. We deploy at the edge or in your local environment where real-time inference is needed, so defect detection and alerts keep pace with production. Where latency is less critical, we run in your cloud, and we tune for the reliability the line demands.

We train on your own sensor and maintenance history, so the models reflect your machines, products, and failure modes rather than a generic dataset. We validate against your historical events before go-live, and your engineers own the models to retune as the line changes.