知識はリストではなく、グラフである。
学ぶ前に依存関係をマッピング。知識を孤立したリストではなく、相互接続された依存関係グラフとして可視化。すべての概念が前提条件と帰結につながり、理解の真のアーキテクチャを明らかにします。
Knowledge is a Graph, Not a List.
Map Dependencies Before You Study.
Accuracy
Nodes
13
Edges
20
Graph dependencies ensure prerequisite-ordered study
Every test question traverses the dependency graph. The graph is the answer engine.
Query Workbench
Retrieve by dependency path, not keyword. Each result shows evidence paths, confidence scores, and explainability — so audit, accounting, and internal controls can decide from the same screen.
Hits
18
Confidence
0.93
Explainability
0.89
Response
268ms
Top Evidence Paths
Onboarding Preview (First 2 Weeks)
Accounting
Extract high-risk issues first during monthly close
Internal Audit
Pre-review control deficiency chains before fieldwork
Management
Cross-check impact scope of policy amendments
Temporal Replay (Root-Cause Tracing)
Scrub through time to trace which update propagated where and when. Use directly as evidence material for incident reports and corrective action documentation.
Selected Tick
2325
Control owners and evidence lines rebuilt
Impact Score
0.86
Affected Nodes
21
Risk Band
HIGH
How to Use
1 Select the incident date
2 Review affected nodes
3 Assign corrective owners immediately
Evidence Trust Lens
Separate graph connectivity from evidence quality. Instantly determine which layers need human review based on reliability scores and drift rates.
Primary Evidence (Contracts, Ledgers, Journal Entries)
Reliability
97%
Drift
2%
Internal Policies & Accounting Memos
Reliability
90%
Drift
7%
Audit Workpapers & Review Records
Reliability
86%
Drift
9%
AI Inference Nodes
Reliability
74%
Drift
19%
Operational Rules (Post-Deployment)
Layers below 0.85 reliability require mandatory human review
Drift above 0.12 auto-generates an update ticket
Monthly AI inference node ratio reported to audit team
Counterfactual Policy Comparison
Compare “what-if” scenarios before production deployment — threshold changes, evidence requirements, gate policies. Evaluate quality and review workload simultaneously.
consistency
78
recall
83
precision
80
reviewLoad
42
Recommended Use Case
Standard daily operations. Balanced trade-off between quality and review cost.
Decision Handoff Flow