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buying

  • Who owns the AI you pay for?

    Code, evaluation sets, prompts, indexes, the data the system learned from: each is owned by someone, and the answer differs between a product, a platform and a build. What to ask so the system you pay for is yours.

  • Fixed price or day rate for AI work?

    Day rates reward time; fixed prices reward outcomes, provided the scope is real. Which to use for consultancy, for a build and for the running of a system, and the one condition that makes a fixed price safe for both sides.

  • What a good AI discovery report looks like

    The deliverable at the end of discovery is a document, so here is what a good one contains, section by section, and the questions to ask of a consultancy's sample before you commission one.

  • What "enterprise" actually means on an AI licence

    The word is on every pricing page and it means different things on each. The five things an enterprise AI tier should give you, and how to tell which ones a given tier actually does.

  • No-training licence terms: what to check before you sign

    The contractual commitment that your data is not used to train the model is what makes enterprise AI tools safe to open. What the commitment actually covers, where it does not apply, and the six things to confirm at contracting.