Documentation / Concepts
Architecture Concepts
Congregation DB operates as layered decision infrastructure.
The architecture is intentionally framed as a series of conceptual layers. Each layer preserves specific properties of the signal environment so downstream systems can reason without erasing origin, meaning or context.
Layered infrastructure
Each layer adds structure while preserving the distinctions required for traceable decision reasoning.
Conceptual layers
Sources
Operational systems, APIs, documents and machine learning outputs generate the raw signal environment.
Truth Lanes
Signals are separated by type to preserve provenance and meaning.
Congregation DB
Enterprise information is organised into a contextual graph structure.
Decision Intelligence
AI systems, analytics and agents consume the graph while retaining traceable reasoning context.
Layered flow
This model moves from raw signal capture to traceable downstream consumption while maintaining audit-friendly context between layers.
Architecture flow
Sources
Operational systems, APIs, documents and machine learning outputs generate the raw signal environment.
Truth Lanes
Signals are separated by type to preserve provenance and meaning.
Congregation DB
Enterprise information is organised into a contextual graph structure.
Decision Intelligence
AI systems, analytics and agents consume the graph while retaining traceable reasoning context.
Language and Reasoning Layers
The architecture also includes an internal language and intermediate reasoning layer so queries can remain stable while CongSynth execution evolves underneath them.
Reasoning boundary
CongLang and CongIR sit between raw signal structure and CongSynth execution so meaning survives across language, planning and downstream use.
Architecture pipeline
A three-layer conceptual path from language expression to reasoning representation to CongSynth execution.
Expression Layer
Language-level reasoning expressions preserve signal meaning before execution planning begins.
Reasoning Layer
A stable intermediate representation carries reasoning semantics across the decision environment.
Execution Layer
The context synthesis engine executes across the contextual graph while lineage and dependencies remain intact.
Extended language and reasoning flow
Raw enterprise signals enter from operational systems, APIs, documents and model outputs.
Signals remain separated by type so meaning and provenance survive downstream reasoning.
The internal language surface expresses reasoning without flattening signal distinctions.
An intermediate representation preserves stable reasoning semantics before execution.
The context synthesis engine retains relationships, dependency structure and lineage across the decision graph.
Downstream systems consume outputs with traceable reasoning context attached.
CongLang queries compile into CongIR which executes through CongSynth while preserving signal provenance and reasoning context.