TQ
TransferIQ
Work Transfer & Supply Chain Risk Intelligence · AS9100 / IAQG / FAA-EASA
AI learning from 1,940 work transfer outcomes
ENV: PROD · ROLE: SR. MANAGER, WORK TRANSFER
Dashboard
TrendIQ 10
DecisionIQ 8
ActionIQ 8
EffectivenessIQ 22
OntologyIQ 18,460
KnowledgeIQ 7
SemanticIQ 7
Global Work Transfer Operations
Continuous risk intelligence across every active work transfer — technical, quality, supply chain, financial, people, program, and governance domains
◊ Knowledge graph: 18,460 linked entities — suppliers, tooling, parts, programs & regulations
Transfer Readiness Index
87%
↑ 4pts this quarter
FAI Evidence Coverage
91%
↑ 3pts
On-Time Tollgate Closure
78%
↑ 6pts
Ramp-Up Cycle Time
-19%
↓ vs. baseline
Open Transfer Risks
9
3 critical
Continuous Intelligence Loop
Signal → Decision → Execution → Outcome → Organizational Learning
● Active across all modules
TrendIQ
10 active signals
→
DecisionIQ
8 initiatives
→
ActionIQ
7 in execution
→
EffectivenessIQ
22 outcomes learned
Transfer Cycle Time — 12-week trend
Weeks from kickoff to production ramp-up approval, by program family
Engineer & PM Time Recaptured
Hours per week saved on evidence assembly and tracking, before vs. after AI
Knowledge Graph Linkage Health
Tooling, documentation & traceability records linked and current
Signal Mix — Last 30 Days
Active signals by risk domain
AI Confidence Distribution
Across all active signals and recommendations
Top Work Transfer Risks — AI-prioritized
Highest-impact items pulled from TrendIQ
AI Operational Copilot
Live workflow optimizations the system is recommending
TrendIQ — Work Transfer Signal Detection
Signals surfaced from tooling logistics, supplier QMS audits, FAI submissions, engineering change logs, and program tollgate systems
● Connected to 6 work transfer systems
Active Signals
10
↑ 3 this week
Pattern Clusters
5
2 emerging
Cross-Domain Correlations
6
3 high-strength
RCAs in Progress
4
Avg conf 86%
AI Recommendations
5
Pending review
Signals 12
Patterns 5
Correlations 7
Root Cause Analysis 4
Recommendations 9
DecisionIQ — Initiative Management
Active work transfer initiatives created from accepted signals, with AI-suggested follow-on tasks
8 active initiatives 5 AI suggestions pending
AI Continuously Recommending
The system is learning from 1,940 historical work transfer outcomes to improve every recommendation below
Initiative owners
94% acceptance
Task owners
89% acceptance
Closure paths
82% accepted
Follow-on tasks
71% accepted
ActionIQ — Execution Coordination
Two-tier Kanban: initiatives at the top, task drill-down on click
Initiatives Kanban
AI Operational Copilot
Live workflow optimizations across the board
Automation Opportunities
Workflows AI can orchestrate end-to-end (with transfer owner signoff)
EffectivenessIQ — Organizational Learning
What worked, what failed, and how the system is getting better at work transfer recommendations
● Continuous learning active
Outcomes Captured
1,940
↑ 86 this month
SME Corrections
34
→ model refinement
Initiative Success Rate
88%
↑ from 79% (Q1)
AI Recommendation Accuracy
91%
↑ 7pts vs baseline
Failed Closures Studied
14
Root-caused
Recent Learning Events
Outcomes from closed initiatives feeding back into the recommendation model
Improvement Over Time
Recommendation acceptance rate by quarter
What's Working (Reinforced)
Patterns the AI is doubling down on
What's Not Working (Down-weighted)
Patterns the AI is moving away from
OntologyIQ — Work Transfer Knowledge Graph
A living semantic model of every supplier, program, tooling asset, regulation, and risk relationship across active work transfers
◊ 18,460 linked entities · 41,200 relationships
Entity Types Modeled
9
Programs, Suppliers, Tooling, Parts, Sites, Regulations, Risks, Initiatives, Owners
Relationship Types
14
requires · owns · impacts · governed-by · supplies · co-occurs-with…
Graph Freshness
96%
Entities updated within the last transfer cycle
Query Accuracy (validated)
93%
Against SME-reviewed answer set
Ask the Knowledge Graph
Not sure where to start? Try a sample question below, or type your own — answers are traced back to the underlying graph nodes and edges.
◊ Grounded answers only
Knowledge Graph Schema
Core entity and relationship types behind every answer
Highest-Connectivity Entities
Nodes with the most cross-domain relationships — usually the highest-leverage risk points
KnowledgeIQ — Institutional & Tribal Knowledge Capture
Tracks where operator know-how, undocumented process nuance, and retiring expertise are captured, at risk, or missing entirely across active transfers
◊ Linked to the OntologyIQ knowledge graph
Knowledge Assets Captured
31
↑ 6 this month
Experts at Retirement/Rotation Risk
6
2 uncaptured
Capture Coverage
68%
Of active transfers with a linked knowledge asset
Avg. Time-to-Capture
11d
↓ from 19d last quarter
Knowledge Graph — Experts, Assets, Programs & Sites
Instance-level view of the graph: who holds the knowledge, what's been captured, and which programs and sites it feeds. Click any node.
At-Risk Expertise
Operators and specialists nearing retirement or rotation, ranked by capture status
Knowledge Asset Library
Captured video, process sheets, and annotated drawings, linked to the program and initiative they came from
SemanticIQ — Semantic Model & Standards Mapping
The taxonomy, relationship types, and terminology model underneath the knowledge graph, plus semantic matching against historical transfers
◊ 7 domains · 21 categories · 30 failure modes
Concepts Modeled
51
21 categories + 30 failure modes across 7 domains
Standards Coverage
89%
AS9100 / IAQG / customer tollgate clauses mapped
Semantic Match Precision
90%
Validated against SME review
Taxonomy Depth
3
Domain → Category → Failure Mode
Terms Normalized
18
Canonical concepts unifying 40+ source-system aliases
Risk Taxonomy
Click a domain to expand its categories, then a category to see the specific failure modes AI is watching for
Semantic Relationship Types
The edge vocabulary the model uses to connect concepts, signals, and standards
Canonical Term Mapping
Normalizes the different names each source system uses for the same concept
Find Semantically Similar Transfers
Search by concept, not keyword — matches on meaning across the historical corpus
Standards Mapping
Internal risk domains mapped to the governing regulatory clause, with current evidence coverage
Add Custom Task
AI has pre-filled this based on the initiative's closure path
AI Pre-fill — Suggestions below are editable. Owner defaults to AI's recommendation.