Documentation / Concepts

Data Ingestion

Enterprise systems generate fragmented signals across many sources.

Enterprise systems generate fragmented signals across many sources. Those sources often reflect different data models, different rates of change and different levels of certainty.

Ingestion surface

Ingestion Surface

Fragmented enterprise inputs converge into a contextual layer that preserves provenance before downstream reasoning begins.

OPERATIONAL DBAPI SIGNALDOCUMENT REPOML OUTPUTCONTEXTUAL LAYERlineage preservedsignal separationGRAPH REASONINGcontextual structure retainedAUDITABLE USEdownstream truth stays legible
The left column represents heterogeneous source environments rather than a single canonical feed.
The centre layer is conceptual: it organises signals while retaining lineage and signal class distinctions.
The right side shows the result of ingestion: auditable graph reasoning and traceable downstream use.

Typical sources

operational databases

APIs

document repositories

machine learning outputs

Contextual organisation

Provenance

Signals enter the platform with lineage intact so downstream reasoning can remain traceable.

Congregation DB organises these signals into a contextual structure that preserves provenance and supports graph reasoning.

Signals remain separated so downstream systems can reason without losing underlying truth.