Costs and usage
What requests cost, what licence counts reveal and how usage can be attributed.
Paid Per Seat, Used Per TaskArticles
Understand AI before you decide.
Explanations, examples and sources on costs, data routes and development. Start with the question that matters to your project now.
Data and responsibility
Where data is processed and what matters when managing access and checking model responses.
Measuring AI Usage Without Sidelining the Works CouncilTechnology and operations
How models work and what turns a model call into a reliable application.
Why a Language Model Is Not a Database Explore the technologyAll articles, by date
Copilot Lives in Office. What Would a Replacement Need?
"Integrated" means four things: where the button sits, the data, the permissions and the operation. A replacement only has to cover the parts people actually use. Where to ask, you can look up.
Why the Same Long Instruction Sometimes Costs Almost Nothing and Sometimes Full Price
A server can reuse the opening of a request instead of recomputing it. That only works if the opening is identical, token for token. From the first differing token on, the saving is gone.
What Switching AI Solutions Really Costs
The simple switching calculation compares a price per user with a price per token. Those are two different things. An honest calculation has five cost blocks and no fixed saving.
Is an AI Model from China a Problem?
The question hides three different questions: where the data goes, how the model behaves, and what the company allows. Only the first one is settled by where the model runs.
Why an Answer Arrives Slower Than the GPU Allows
For every single token, the GPU re-reads the entire set of model weights just to compute that one token. Speculative decoding lets a small model guess ahead and saves exactly that wait.
Data Classification: Why Fixed Access Tiers Beat Prompt Filters
An AI system that scans every prompt for sensitive content is betting on detection. A system that fixes access rights beforehand needs no detection at all. Why the difference matters for an AI data-path review.
