A structured, low-risk process for evaluating and deploying edge AI prediction technology on your existing equipment. Start small, validate fast, scale with confidence.
We begin with a focused discussion to understand your process, existing sensors, and what you want to predict or detect. Together we identify which approach fits your challenge best.
No commitment required. This step helps both sides evaluate whether our technology is the right fit.
Using a sample of your real process data, we develop a working AI model and benchmark it against your target metric. Our technology trains in seconds — you see concrete results within days, not months.
This is the moment you see whether the technology works on your specific process, with your actual data.
Once the benchmark confirms feasibility, we develop a production-grade AI model optimized for your specific process conditions, sensor configuration, and target hardware. This includes hyperparameter optimization, validation across operating conditions, and performance documentation.
The trained model is compiled into lightweight software designed to run directly on your existing equipment — industrial PCs, PLCs, SCADA systems, or microcontrollers. No cloud subscription, no GPU, no new hardware. Your data stays on-site, and inference runs in sub-millisecond time.
The goal of each project is deployable AI software — not a dashboard, not a cloud subscription.
Optimized for your process data. Compiled as lightweight software ready to run on your target device.
Accuracy metrics, validation results, and comparison against baseline methods. Clear evidence that the model works.
Technical documentation for integrating the AI software into your existing control system or data pipeline.
Start with a non-binding discussion and a small data sample. No infrastructure setup, no long-term contract to begin.
Our AI trains in seconds. You see benchmark results on your own data within days — not the months typical of deep learning projects.
The result is software that runs on your hardware. No cloud dependency, no ongoing subscription required for inference.
Once a model is proven, it can be adapted to new units, lines, or sites with minimal additional data — reducing rollout time from months to days.
Tell us what you want to predict, detect, or forecast. We can assess feasibility together and identify a concrete next step — typically a rapid benchmark on your data.
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