Most AI projects run into the same problem: a capable model, a motivated team, and a data set that has accumulated for years without cleanup. The wrong answers usually don't come from the model — they come from the data fed into it. Teams often assume the fix is "a better model." It almost never is. The model is rarely the problem — the data it receives is. Here's a rule that's hard to accept but always holds: AI doesn't fix your data. It repeats it. If documents contradict each other, the...