Your enterprise
is alive.
Every commit changes the architecture.
Every hire shifts capabilities. Every regulation creates new obligations.
Your enterprise is a living, self-organizing system, but you're navigating it with static diagrams and quarterly reviews.
The Problem
Two universes
that can't talk.
Business Universe
Concepts. "Customer Onboarding," "Loan Approval," "KYC," "Lending Process".
Things executives, domain owners, and compliance teams use every day.
This is what the business means.
Technical Universe
Code, databases, APIs, microservices, schemas.
Things engineers build and maintain.
This is what the business runs on. These two share zero common language.
Traditional data catalogs try to bridge this bottom-up: catalog tables, hope business meaning emerges.
It doesn't.
The Inversion
Start with meaning.
Link to everything.
Coherence inverts the traditional approach.
It starts with human-defined business concepts and then mathematically links every technical asset in the organization to those concepts.
The result is a living, inhabited digital twin, a conscious model of the whole.
From strategy at the top to source code at the bottom.
The Full Chain
The Knowledge Fabric
A map that's never stale.
After ingestion and linking, the platform holds a complete, mathematically grounded picture of your organization.
Every concept is approved by a human. Every link has a confidence score.
The map updates continuously.
285
Business concepts
Banking simulation
630
Technical assets
Parsed, linked, scored
99.7%
Coverage
Concept ↔ asset match
The Shift
System of Action,
not System of Record.
Most semantic tools observe and report.
The Kinetic Layer writes back to source systems.
Coherence is not an analytics overlay.
It is an operational platform that acts on the knowledge it holds.
What changes
System of Record
- ·Observe
- ·Report
- ·Wait for humans
- ·Eventual consistency
System of Action
- Detect drift autonomously
- Simulate consequences
- Surface recommendations
- Strong consistency + write-back
Multi-Layer Intelligence
Agents at every layer.
Each with a purpose.
Not one AI. A network of specialised agents with agency, each inhabiting a different layer of the ontology. From answering questions to building 3D worlds to autonomously patrolling your architecture for drift.
Every agent is grounded in the knowledge graph. Every output is traceable.
Explorer (OAG)
Three-phase query pipeline: plan the traversal, retrieve evidence from the graph, synthesize a cited answer. Every claim traceable to a specific node.
World Builder
Eight coordinated agents that read the ontology and construct a navigable 3D representation. Spatial layout, entity placement, narrative context, connection routing.
Projection Engine
Comprehend the domain, synthesize a Use Case Graph, compute influence edges, enrich with deep graph RAG across all four architecture layers.
Domain Specialists
Architecture Critic, Cost Optimizer, Security Auditor, Innovation Scout. Autonomous patrol with interest-field navigation, structured debate when they converge.
Consequence Simulation
Fork the World.
Create an isolated copy of the digital twin.
Introduce a change.
Deprecate a service, add a compliance rule, change an API.
And see the full impact cascade across the entire graph.
Before touching anything real.
One simulation answers
- What breaks if I deprecate this microservice?
- Which teams are affected by this regulatory change?
- What is the blast radius of this cloud migration?
- Does this product launch conflict with existing business processes?
Early preview. production 3D assets in active development
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