The improvement cycle in traditional AI can run months long, requires thousands of labeled examples, and still doesn’t guarantee results. For industries like energy infrastructure, where the most critical defects are also the rarest, that’s not a minor inconvenience. It’s a dead end.

So we built our own patent-pending AI to solve it.

This whitepaper covers our Adaptive AI approach – which flips the model entirely: instead of collecting data, labeling it, training for weeks, and hoping the output reflects what your experts actually meant, domain experts simply show the system a few examples. It learns. It adapts in real time. And when better foundation models come out, performance improves automatically: no retraining, no re-labeling, no waiting.