Starting an AI transformation without a big-bang rewrite

When an institution asks for an AI transformation, the temptation is to start with a platform decision. We start with the process instead: who does what today, where the data lives, and what done means.

Map the work first

• List the recurring tasks that eat the most hours.
• Mark which of them depend on reading documents or data, and which need judgment.
• Note the systems and permissions each task touches.

Ship one flow

Choose a single flow with a clear owner and measurable output. Build it with Claude in the loop, put it in front of the people who run it, and adjust. A working flow teaches more than a strategy deck.

Transformation is the sum of flows that work in production, not the number of pilots started.

Keep the knowledge in-house

Every flow we deliver comes with the plan, the review history, and training for the team that will own it. The client leaves with software and the skill to extend it.