AI belongs in a workflow when it helps solve a defined problem. The work begins with the task, available data, evaluation criteria and risk—not with a model name.

Possible engagement areas

AI feature and application prototyping
Model selection and integration planning
Inference and deployment workflows
Evaluation, monitoring and documentation
Human review and fallback design

Built around constraints

Requirements such as latency, cost, privacy, reliability and maintenance determine the design. A prototype is labeled as a prototype until it has passed appropriate testing in its target environment.