Most English-language analysis of Chinese AI cannot tell 王伟 from 王薇, and counts a paper as "Chinese" because an author has a Chinese name. These tools read the papers themselves: every affiliation line, every funding acknowledgement, every name in every script. Each call comes with its evidence and a measured error rate.
Who is building China's AI, who pays for it, and how do we know?
Two tools, one pipeline. The Name Engine matches a person across the scripts and dialects a Chinese name travels through. The Paper Pipeline reads every new AI paper on arXiv and answers where the authors work, who funded the work, and which records are the same person, grading every link by the strength of its evidence. A human reviewer sees each decision with its reason, and can override the machine.
Matches one person across every spelling of their name.
Characters, Pinyin, Wade-Giles (Taiwan), Cantonese (Hong Kong, Macau) and the Hokkien, Teochew and Hakka spellings of Singapore and Malaysia. Every comparison returns a level, a weight of evidence, and a reason a reviewer can read. A mismatch it cannot read is never counted against a match.
Reads every new AI paper for who wrote it and who funded it.
Maps each affiliation to an institution and the place it names, extracts every funder and its country, decides scope under saved definitions, and links author records into people. Each identity link is graded Confirmed, Probable or Unresolved, and the matcher errs on the side of caution by design.
The Rhetoric Engine reads Chinese and Russian AI discourse for framing and narrative, not just facts: the recurring rhetorical moves, how a phrase or narrative propagates across outlets and up the state hierarchy, and the gap between what is said to domestic and foreign audiences. It combines language models with static techniques to stay both effective and efficient. In development; a growing suite.
The source is private; this is what the tools do and how well they do it. For a live walkthrough, a commissioned analysis of a corpus, or code access, get in touch. Available for roles and consulting in AI research, evaluation, and China-facing intelligence.
Every headline number comes from a random sample or a held-out set, never from examples picked by hand. A separate model pass labelled the sample blind to the tool's output, and a human re-check is under way. Privacy by design: researcher data never leaves the analyst's machine, and no real researcher appears in any test.