What we look for before recommending an AI solution

The easiest mistake in AI consulting is recommending AI because a client asked for it, not because the workflow calls for it. Before we scope anything, we look for a specific pattern: repeatable decisions or documents, enough historical data to learn from, and a clear cost to the manual version of the task today.

When those conditions hold, the case for AI is usually strong and the ROI is measurable. When they don't, we say so — sometimes the better recommendation is a simpler automation, or no change at all.

This is also why we build our own product, HomePro, on the same foundation we recommend to clients. It keeps us honest about what's genuinely production-ready versus what only looks good in a demo.