Documentation
Documentation
Technical concepts and architectural foundations behind Congregation DB.
These documents introduce the conceptual architecture behind Congregation DB. Detailed developer documentation will expand as the platform evolves.
Congregation DB is a deterministic-first graph infrastructure designed to support provable AI decision systems. These documents introduce the conceptual foundations of the platform.
Provenance
Signals retain origin and lineage so decision systems can inspect where information came from.
Separation
Different signal classes remain distinct instead of being collapsed into a single undifferentiated layer.
Provability
Decision outputs remain traceable, replayable and auditable across evolving enterprise contexts.
Browse the docs
The documentation is structured as a conceptual system rather than a marketing narrative. Each page focuses on an architectural idea that explains how the platform preserves context for serious decision environments.
Foundations
Start with the platform purpose, operating model and core capabilities.
Foundations
Understand the provenance, separation and provability constraints.
Concepts
Review the layered model used to preserve context across decision systems.
Concepts
See how decision environments combine enterprise signals, context and reasoning layers.
Concepts
See how deterministic, probabilistic and derived signals remain distinct.
Concepts
Understand why signal origin, lineage and reasoning context must remain attached in decision systems.
Concepts
Follow the conceptual ingestion surface from fragmented source signals to contextual structure.
Concepts
Explore the context synthesis engine used for traceable reasoning across the decision graph.
Concepts
Understand how entities, relationships and signals create meaning inside the decision graph.
Concepts
Understand why relational decision environments benefit from graph infrastructure.
Concepts
Move through the conceptual flow from source signals to decision intelligence.
Concepts
Review the internal language layer used for contextual reasoning across separated signals.
Concepts
Understand the intermediate reasoning representation between language and CongSynth execution.
Concepts
Review the conceptual path from query expression through CongSynth reasoning into decision output and replay.
Concepts
Compare why legacy data stacks were not designed for provable decision environments.