What a graphis for.
Six problems Fortune 500 CTOs kept naming, and one job a graph does worse. The answer is a route, not a passage.
What it solves.
Fifty conversations with Fortune 500 CTOs came back as the same six. Each card is one of them, and what the graph does about it.
Proving what the AI said
Answers about your own code come back as opinions. Here every answer is a path you can open, evidence tagged on each edge, so audited work can trust it.
One map of the code
Hundreds of repos, teams across countries, no shared view. One graph across all of them, so a change that crosses a boundary shows up before it ships.
What a change breaks
A guided diff shows the lines, not what depends on them. The graph follows every caller, config and test out from the change, so review covers what it reaches.
Token spend with a result
Seats, tokens and GPUs climb with nothing to show. An assistant that queries the graph stops pasting whole files, and every query is a line you can account for.
Answers beyond the code
The answer sits across repos, wikis, contracts and decades of documents. The graph spans both sides, so nobody stitches it together by hand and gets it wrong.
Never re-learn the codebase
Each engagement or modernization starts from scratch by hand. The map is built once and kept current, so what one team learns compounds into the next.
Where it will not help.
If the job is fuzzy search over a large body of prose, embeddings are the better tool and Graphify does not try to beat them at it. A graph is for questions about how things connect.
It is also not a substitute for reading the code. It says what calls what and where each claim came from. Whether it should have been built that way is yours to judge.