AI features that hold up on real business data
The gap between an AI demo and an AI feature is everything that happens when the model is confidently wrong. That gap is the work.
An AI feature that works 90% of the time is not 90% of a feature. It depends entirely on the other 10%, and that is a design decision rather than a model choice.
On a property inspection platform, AI analyses uploaded photos and video and drafts technical findings. What it does not do is write the report — an inspection report is a professional liability, so the inspector stays the author. The AI suggests; they apply it deliberately.
On a document extraction pipeline, a confidence gate routes uncertain cases to a human. Knowing when the model is unsure is worth more than being right slightly more often.
- →Confidence gates where the stakes justify a human
- →Cost control — model routing, caching, prompt structure
- →An honest answer on whether AI is the right tool at all
Something holding you back?
New build, rebuild, or adding AI to what you already have — I'll take a look and give you an honest perspective.