AI systems

For organizations exploring a bounded use of AI, such as finding answers in internal documents, drafting routine material, or sorting incoming requests. Begin where a repeated task has a clear input, a useful expected output, and a person who can check the result. AI is not a fit for every problem, and quality depends on the source material and review process.

Work can include use-case selection, source and data review, workflow design, model evaluation, a small prototype, test cases, human review points, and operating guidance. We discuss data sensitivity, access, failure handling, and ongoing model or provider costs before implementation. No accuracy or savings outcome is assumed in advance.

We first map the task and agree what a useful pilot would demonstrate. The team reviews examples and edge cases, then decides whether to refine, expand, or stop. Scope and any production deployment requirements are confirmed for each project.