Anneal Model
A domain-specialized embedding and retrieval engine for semiconductors.
Six source streams are aligned into one vector space, and questions and documents are measured on the same scale to find the evidence. Retrieval accuracy becomes answer reliability, so this engine sets the ceiling for the whole product.
Data takes one path from arrival to decision artifact.
Six source streams enter the same pipeline. Anneal holds the retrieval scale at the middle of it, and reasoning runs on top of that.
Questions and documents are measured on the same scale.
Learning from domain data and the review history of its users, it sets the distance between semiconductor terms and concepts the way engineers in the field read them. The finer that scale, the better the evidence on the first screen.
Each step to the right is harder to copy.
The raw material is public. What follows it — the processing, the experience, and the assets that accumulate — opens a gap that widens with time.
Raw material
Six public and internal source streams collected through one pipeline. The collection is reproducible at any time.
Processing
Source text is restructured into one comparable row. Conditions, measured values and the location of the evidence sit in the same table.
Experience
Work is delegated to role-specialized agents in a problem-scoped workspace. It fits the organization more closely the more it is used.
Lock-in
Internal material and decision history join under tenant isolation. As artifacts accumulate they become an asset only that customer holds.