[insight]
Why architecture, governance, and unit economics belong before a prototype, not after it.
A prototype shown as a demo creates expectations that are expensive to meet. Stakeholders see a working system and assume production is a matter of polish. The team knows the prototype has no pipeline, no controls, and no cost model. The gap is where programmes lose a year.
Decide early where data lives, how models are served, what the integration points are, and which platform runs it. These are small decisions at the start and large rebuilds later. Our partnerships with Databricks, Snowflake, and Google Cloud exist so these choices can be made with production in mind.
Access, retention, evaluation, monitoring, and incident response cost little to design at the start and a great deal to retrofit. A prototype that already runs under the controls production will need can move to production without a second approval cycle.
Model the cost per outcome — inference, licences, data, and people — at the volume production will see. Some use cases fail this test and should be stopped before a prototype flatters them.
When these three are in place, the prototype and the production system are the same codebase at different stages. There is no rebuild, no hand-off to a different team, and no moment where a demo has to be explained away.
Tell us about the decision or workflow you want to change. We'll come back with an honest view on whether it's worth proving, and what it would take.
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