Seshat, a large historical databank, alongside EMEWS, a supercomputing modeling tool.
The engine treats it as the empirical bedrock — hard data — for studying how social complexity develops.
Seshat covers 800+ societies across 10,000 years and uses statistical analysis (PCA) to find shared pathways of rising complexity; EMEWS is a Department of Energy high-performance-computing platform for agent-based modeling.
It grounds the engine's big claims about history in a broad, testable evidence base rather than guesswork.