The map covers every company, fab, product and material in the semiconductor value chain, and what actually moves between them. We build it from the public record and source every claim down to the sentence. Ask it what you would otherwise pay an expert network to tell you. Implement it into your own agents over MCP. When the record runs out, it tells you the answer is not established. It does not guess.
Take any two companies in semis. We want to tell you what moved between them, in what quantity, at what price, under what relationship, over what period, and from which documents. That one question is the whole product. Every answer opens back to the sentence it came from.
EDA and IP, design houses, foundries, memory, OSAT, equipment, subsystems, materials, gases, wafers, substrates, distributors, hyperscalers, end markets and the governments that intervene. Plus the fabs and products that connect them. If it shapes what a name earns, it belongs on the map.
We label numbers measured, derived, assumed or unknown, and we never collapse an unknown into a tidy point estimate. Where the truth is private, you get a sourced range or an honest blank. A model may find a span and map vocabulary. It may never invent a magnitude. We audit for that and quarantine what fails.
A map this wide falls out of date the moment you stop reading. Nobody can staff that. So we train our own models to maintain it, on evidence mined from the map itself. They read everything that arrives, every day, and they get sharper as the map grows.
One family, built on evidence nobody else holds. We measure every figure here on a frozen eval set we hold back, and we run it again before any model ships. A regression cannot slip through quietly.
General models invent supply chains because nobody can check what sits underneath. We build the part you can check. A corpus held on cursors. Claims pinned to spans. Entities that carry their aliases. An answer path that fails closed when the record cannot support the question. We started with semiconductors because the chain is deep, global and unusually well documented. The same machinery travels to other industries, and that comes later.
We pull from a standing corpus of 1,979,194 documents. It sits on durable cursors, so we can read all of it again every time the models improve.