We identify where your process is losing value — quality, efficiency, scrap — and deliver a measurable answer that justifies an investment or operational decision. Real data from your process. No generic demos. No commitment before we've defined the problem together.
Before any analysis, we establish whether the problem is real and measurable. An on-site visit, available data, shared success criteria. If there is no clear economic case, we say so immediately. No financial commitment at this stage.
No generic datasets. We collect data from your production line, train the model on your components, and measure with a controlled experimental method. Typically 4–6 weeks from data collection to deliverable.
Measured accuracy, estimated economic impact, identified limitations, clear recommendation. The deliverable is designed to support an investment decision — not to open new questions.
The data exists — machine logs, process parameters, shift reports. But nobody has ever analysed the correlation between those variables and quality output. The answer is usually already in the data you have.
Sampling inspection works as long as volume is manageable and operators are rested. When pace increases or geometry becomes complex, human variability becomes the bottleneck. You want to know whether an AI system can do better — on your actual parts, not on a demo.
Before allocating budget on a system, an acquisition, or a technology partner, it's worth knowing whether the technology holds up on your real data. An independent assessment reduces the risk of investing in a promise that doesn't survive contact with production.
Anomaly detection system for automated visual inspection of discrete components — machined metal parts, castings, CNC-finished parts. Trained on conforming part images: no labelled defect dataset required. The architecture integrates with existing plant infrastructure — PLC, MES, motion control — rather than operating as a standalone layer. Currently in validation with a Tier 1 automotive manufacturer on cylindrical geometries with reflective surfaces.
A 30-minute call to establish whether there is a measurable economic case. No commitment. An honest answer — even if the answer is no.