03 · The Edge
Most “AI research tools” are a prompt wrapped around someone else’s chatbot. Yajur isn’t. It’s a purpose-built engine for business scholarship: a corpus nobody else has cleaned, a reading method built for how this field reports evidence, and checks that never let a claim outrun its source. The edge isn’t any one model. It’s the system around the models, and that stays ours.
The engine
Not a prompt wrapped around a general chatbot. Yajur is a purpose-built engine with one job: reading business research the way a reviewer does, not the way the open web does. Models are components inside it: benchmarked, interchangeable, and never trusted on their own word.
The corpus
One clean boundary (148 journals across the UTD-24, the FT50, and the AJG top tier) and the conventions that come with them: how methods are reported, how findings are hedged, what counts as evidence. The noise never gets in, so it never has to be filtered out.
The method
The curation, the reading and checking method, and the loop that keeps it honest. That’s the part we keep. It’s the difference between a tool that sounds right and one a scholar can defend. It isn’t in this deck, and it won’t be.
Trust
Every claim carries the sentence it came from, checked in code against the scholar’s own licensed copy, and “not reported” always beats a guess. For an audience that abandons a tool after a single confident error, that discipline isn’t bolted on top. It’s the design.
How the instrument gets sharper with every cohort
Every cohort of papers makes the instrument sharper: a gap that can’t be prompt-engineered shut.