When the answer needs a real trained model, not a prompt: forecasting the future, scoring risk, or seeing what a human would miss in an image.
A language model can't tell you next month's demand or spot a hairline crack in a facade. For those, we train and deploy purpose-built models — forecasting, anomaly detection, computer vision — sized for your data and your accuracy bar.
These run where you need them: a GPU pool in your cloud, batched and autoscaled, with versioning and confidence thresholds that route uncertain calls to a human.
Not always. We'll tell you honestly whether your data is enough, and use pre-trained models or augmentation where it makes sense.
Your cloud or on-prem — your data and the GPU bill both stay with you.
Tell me the problem. I'll show you whether this is the right tool — and how fast I can prove it.
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