Architecture diagnosis before any AI recommendation
Most AI engagements skip the hard part. We map your stack's failure points first — then decide where AI actually helps.
AI solves specific problems. We find yours.
Repackaged templates assume your stack is ready. It rarely is. We audit data pipelines, model boundaries, and API surface area before writing a line of integration code.
The output is a documented architecture decision record — what to build, what to defer, and what AI cannot fix in your current system.
From audit to written decision record
Map the stack's actual state
Isolate what AI solves and what it hides
A decision record your team owns
We separate genuine AI leverage from complexity it would mask. Each gap is traced to a root cause, not a product recommendation.
You receive a written ADR: decisions made, trade-offs documented, implementation path defined. Not a slide deck. Not a handoff.
Senior engineers review your data flows, model boundaries, and API surface area. No assumptions from a template.
Know exactly where your architecture stands
Senior engineers, written output, no agency overhead. Engagements start with a direct technical conversation — no sales intermediaries.