We build AI products. Then we build yours.

A few months ago, a logistics company came to us wanting to automate their customer complaint handling. Volume was high, the team was stretched, and someone had seen a competitor demo a chatbot at a trade show. We recommended against it. Not because the technology could not do it. It could. But when we mapped where the complaints were actually coming from, about 80% traced back to one recurring problem in their dispatch scheduling. Fix the scheduling, and most of the complaint volume goes away

Most AI project briefs contain three things: a description of what the business wants, a rough sense of the technology involved, and a lot of assumptions that nobody has written down. The build happens. The assumptions surface. The result was not quite what anyone actually needed. A good brief is the document that makes those assumptions explicit before anyone starts writing code. It is not a long document. It is not a technical specification (that comes later, once a developer has reviewed yo

Most AI projects don't fail because the technology doesn't work. They fail because nobody agreed on what it was supposed to do. The brief was vague. The scope kept shifting. The developer built what they understood, which was not quite what the client meant, which was not quite what the client's team actually needed. Six months later, something technically functional exists and nobody quite uses it. This is the most common failure mode in AI implementation. And it is almost entirely preventabl