AI
Piloting AI in your business without the risk
· 4 min
Most failed AI projects start too broad. Successful pilots pick a single workflow with a clear before-and-after measure.
Build an evaluation set
Collect real examples and expected outcomes before building. This turns “it seems good” into a measurable accuracy figure.
Design the fallback
Decide what happens when the model is unsure. Routing uncertain cases to a person keeps quality high while you learn.