Decision Graph
An enterprise AI auditability architecture concept that uses graph structures to link facts, evidence, rules, responsible parties, and decision outcomes. This approach makes AI conclusions traceable, auditable, and reproducible, distinguishing it from the static text retrieval approach of conventional RAG systems.
Timeline (last 90 days)
The underlying mechanism of the memory solution uses a three-layer structure: organized records (the current truth), a decision graph (the process of arriving at the current state), and the complete history (retaining everything and searchable).
In the decision graph, each decision is a line containing the date, the reason stated at the time, and the options that were defeated; a reversal is a new line, and history is never rewritten.
A decision graph is a queryable network that connects facts, evidence, rules, responsible parties, and outcomes.
When data quality is unstable, deployment of a decision graph should be deferred, because the graph will amplify chaos rather than automatically fix it.
All Facts (4)
The underlying mechanism of the memory solution uses a three-layer structure: organized records (the current truth), a decision graph (the process of arriving at the current state), and the complete history (retaining everything and searchable).
50%UnverifiedIn the decision graph, each decision is a line containing the date, the reason stated at the time, and the options that were defeated; a reversal is a new line, and history is never rewritten.
50%UnverifiedA decision graph is a queryable network that connects facts, evidence, rules, responsible parties, and outcomes.
50%UnverifiedWhen data quality is unstable, deployment of a decision graph should be deferred, because the graph will amplify chaos rather than automatically fix it.
50%