Comparisons
The decisions that decide whether an AI project works
Compared criterion by criterion, with a stated verdict — including the cases where our honest recommendation costs us the engagement.
- Stated verdicts
- No hedging
In short
These pages compare the decisions that most often determine whether an AI project succeeds, criterion by criterion, and then commit to a recommendation. Each one includes the cases where our recommendation is to do the thing that earns us less — buy a platform instead of building, or skip a use case entirely — because a comparison that always concludes in our favour is not a comparison.
Comparisons
Decisions worth getting right
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RAG vs Fine-tuning
The two are commonly treated as alternatives. They solve different problems, and picking the wrong one wastes a quarter.
8 criteria -
Buy a platform vs Build custom
Vendor platforms win more often than agencies admit. Here is the line, drawn on total cost over two years rather than on licence price.
9 criteria
Next Step
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