Intelligence Interface

Turn a client question into a consulting reasoning path.

The Navigator is not positioned as search and not yet as a full AI advisor. It is the first explainable interface for answering: what should we look at next?

It uses the local knowledge graph to recommend relevant language, framework layers, thinking paths, and consulting questions. The goal is reasoning support, not content lookup.

Clarify the problem

Start from a client question, not from a list of concepts.

Find the reasoning path

Connect the question to framework layers, methods, and consulting questions.

Suggest the next move

Point toward assessment, prototype, delivery assets, or deeper language references.

Governed recommendations

Methods, assets and evidence to use next

These recommendations are ranked from the governed registry, not generated as unsupported advice.

methodseed5 evidence refs

AI-Ready Data Foundation Assessment

A reusable consulting pattern for assessing whether an enterprise data foundation can support GenAI, RAG, GraphRAG, semantic governance, and AI-assisted decisions.

Pathway layer: Curated Data
Delivery stages: Assess → Discover → Design
Confidence: 70

Next action

Turn assessment dimensions into scorecard questions

methodseed0 evidence refs

Digital Twin 2.0 Semantic Governance Assessment

A one-day PoC pattern for assessing whether a digital twin data foundation is ready for semantic layer, knowledge graph, GraphRAG, AI agents, and decision support.

Pathway layer: Semantic Layer
Delivery stages: Assess → Discover → Design
Confidence: Not scored

Next action

Create one-day workshop facilitation checklist

methodseed0 evidence refs

Knowledge Graph Readiness Assessment

A reusable consulting pattern for assessing whether an organisation is ready to build and operate a knowledge graph for enterprise AI, GraphRAG, digital twin, or semantic governance use cases.

Pathway layer: Knowledge
Delivery stages: Assess → Discover → Design
Confidence: Not scored

Next action

Define minimum viable graph acceptance criteria

methodseed4 evidence refs

Source-to-Scene Pipeline

An emerging method for transforming heterogeneous source data into a coherent, governed, semantically connected operational scene for AI, simulation, and decision support.

Pathway layer: Knowledge
Delivery stages: Discover → Design → Prototype → Govern
Confidence: 62

Next action

Pilot the method against a second, independent reference scenario to test generalisation beyond a single case -- still the binding next step; the 2026-07-08 data expansion deepened GBlocks but does not itself satisfy this

Reasoning Interface

Ask a client delivery question

Relevant Language

Where the question lands

SemanticsSemantic Layer

A governed meaning layer that removes ambiguity across business data, real-world representations, digital twins, knowledge graphs, and AI systems.

KnowledgeKnowledge Graph

A connected representation of entities, relationships, context, and evidence for reasoning and discovery.

RealityReality Mapping

The discipline of mapping real-world objects, events, places, and responsibilities into trustworthy digital representations.

SemanticsOntology

A structured model of concepts, relationships, constraints, and meaning within a domain.

Framework Path

Suggested thinking route

Reality MappingRepresentationIdentityRaw DataCurated DataSemantic LayerKnowledge GraphAI Reasoning

Thinking Path

Concept-to-concept reasoning

Reality MappingFeedsOntology

OntologySupportsAI Reasoning

Consulting Questions

Questions to ask the client

Which source data needs to be curated once before semantic definitions can be reused many times?
Which ontology concepts need to become reusable definitions for delivery teams?
Which semantic definitions should be materialised into connected knowledge?
What metadata is required to prove that a semantic definition is reliable?
Which business concepts should be available as APIs rather than buried in databases?
Where does AI currently rely on implicit or inconsistent business meaning?
What schema is needed before graph connections can be trusted?