Start with meaning.
Not with data.
Data catalogs start at the physical layer and hope business meaning emerges. It never does.
Coherence starts with what your business means, building a conscious model defined by humans, locked by governance.
And links everything else to it.
Closed World Assumption
If it's not in the model,
it's unknown.
Traditional semantic web uses the Open World Assumption.
Anything not stated is possible.
That's fine for academic research.
It's catastrophic for enterprise operations.
Coherence enforces a Closed World: if something is not modeled, it is treated as unknown.
Not as acceptable.
This is what regulators need.
Open World (Academic)
"We don't know if this service is compliant, so it might be."
Closed World (Coherence)
"We don't know if this service is compliant, so we flag it."
Domain Packs
Minutes, not months.
Pre-built libraries of standard business concepts for your vertical. Load them, get immediate working vocabulary, then customise. No ontology workshops.
No 6-month projects.
Banking Pack (Live)
Commercial Banking
BSA/AML
Regulatory Compliance
Payments & Cards
Loan Origination
Customer Mgmt
Risk Analytics
Fraud Detection
Why This Is Different
Data catalog vs. ontology.
| Dimension | Data Catalog | Coherence |
|---|---|---|
| Starting point | Physical layer. Tables and columns | Human-defined business concepts |
| Direction | Bottom-up | Top-down (ontology-first) |
| Semantic linking | Manual tags and glossary | Mathematical (HyDE + cosine similarity) |
| Code depth | Metadata only | Full source code, 9+ languages, AST-level |
| AI query layer | None or basic chat | 3-agent grounded swarm with citations |
| Visualisation | Flat tables and lineage | Living, inhabited 2D/3D navigable digital twin |
| Cost | $100K+/year | ~$5/month maintenance at scale |
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