CodeMap AI

Auto-generate readable architecture docs and call graphs for AI-generated codebases

Problem

In teams where nearly all code is AI-generated, members cannot explain how the system is split, what the sequence flow looks like, or what each API and message queue is responsible for — they can only give a 50-word summary. Engineering standards and observability work stall because nobody sees the whole picture.

Solution

Connect a repo and automatically scan directories, entry points, routes, message queues and external calls to produce module responsibility notes, key sequence diagrams and API/MQ inventories. Incremental updates after each commit flag modules missing docs or tests. Output doubles as a starting point for ADRs and specs.

Users

Small and mid-size engineering teams heavy on AI-generated code, plus newly onboarded engineers

MVP

Scan repo to build module inventory and dependency graph; detect entry points, routes and message queues; generate Markdown architecture summaries; incremental updates with diffs; export Mermaid diagrams

Revenue

Subscription per repo; per-seat team plan; free for open-source projects

Why now

AI code generation inflates code volume while shrinking understanding, and teams urgently need to rebuild mental maps cheaply; LLMs make auto-generated architecture docs viable for the first time