Building an AI MVP in Weeks, Not Months

The biggest risk in AI projects is spending months building before learning whether the underlying idea actually works well enough on real data.

We scope AI MVPs around a single, narrow use case, using off-the-shelf models and existing data, aiming to have something testable with real users within a few weeks.

This early feedback shapes the full build far more usefully than any amount of upfront planning, and often reveals which parts of the original idea need to change.