Case Studies
How teams unlocked AI on codebases
they've been building for years.
These aren't toy examples. These are real production systems, real teams, and the honest story of what it took to get AI working reliably on them.
CONFIDENTIAL: 18 Years of Mission-Critical Code Made AI-Ready
A defense & security client had accumulated nearly two decades of production code across Windows, Android, iOS, and Linux platforms. The codebase was battle-tested but sprawling, inconsistent naming, undocumented business logic, and zero AI tooling. As part of the engagement, Stature migrated the full stack from .NET/C# to Node.js and React, and moved infrastructure to a modern cloud hosting model, reducing hosting costs by 1,200%. Stature then spent 10 weeks standardizing 340,000 lines of code, writing inline documentation, normalizing patterns, and configuring a domain-tuned Cursor workspace. Their dev team now ships features with AI assistance that previously required three developers and two weeks.
Complex Mobile Platform: AI Copilot in a Multi-Platform Nightmare
A technology director came to Stature with a fragmented mobile codebase, Objective-C mixed with Swift, Java alongside Kotlin, and a shared business logic layer that had been copy-pasted between platforms for years. AI tools were producing dangerous hallucinations because the code gave no consistent signal. Stature ran a 6-week consolidation: unified patterns, cross-platform documentation, shared contract definitions, and a custom Claude project context. The team now uses AI to extend features across both platforms simultaneously, what used to require separate iOS and Android specialists.
Growth-Stage SaaS: Taming Five Years of Move-Fast Code
A B2B SaaS company had grown fast, too fast for their codebase to keep up. Five years of startup velocity left them with inconsistent API patterns, undocumented database schemas, and a Node.js backend that Copilot actively made worse. New developers were spending their first month just mapping the system. Stature ran a documentation-first pass: auto-generated schema docs, API contract standardization, and a structured onboarding context for AI tools. New developers now reach full productivity in a week. AI-assisted feature work is reliable enough that the team ships two-week sprints in three days.
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