We excavate, maintain, and migrate legacy codebases.

Quickly, efficiently, and as safely as can be designed.

Cumberland Laboratories is an applied AI research lab in Portland, Maine. Our work targets the hardest problem in long-lived software: understanding it. Before changing a system, we recover a semantic map of it — what each part owns, what it must preserve, what breaks if touched. Only then do we change it, under high supervision: human architectural control over every AI-assisted step.

The method is a new take on older ideas — David Parnas’s module guides and information hiding, Edsger Dijkstra’s separation of concerns — rebuilt for an era in which machines can write code faster than humans can reread it. The maps live in your repository, in plain text, under version control. The evidence of every change stays on infrastructure you own.