Ontology-based AI Operations & Knowledge QA Platform
A structure where the basis of every answer is preserved.
A next-generation platform that supports stable AI operations and knowledge QA at the same time. S-HAP hybrid extraction, a 3-layer validation gate, SSOT knowledge graph, semantic-drift monitoring, and Vector+Graph hybrid retrieval — reconstructed in the AX Lab tone.
More important than generating an answer is the structure that preserves the basis of every answer.
— Technical Intent
A structure where the basis of every answer is preserved.
Ontology-based AI operations manage enterprise knowledge as a single source of truth — making source, change history, and semantic drift of every answer traceable.
— Architecture · 6 layers
Architecture
- 01 · Extract
S-HAP Hybrid Extraction
Extract entities, relations, attributes from docs and web.
- 02 · Verify
3-Layer Validation Gate
Stage syntax, semantics, and operational rules.
- 03 · Graph
SSOT Knowledge Graph
Store verified knowledge as the reference graph.
- 04 · Search
Vector + Graph Retrieval
Combine vector similarity with graph traversal.
- 05 · Monitor
Semantic Drift Monitoring
Detect knowledge changes and answer-pattern shifts.
- 06 · Operate
AI Ops Dashboard
Visualize accuracy, fallback rate, and knowledge conflicts.
— Flow · 5 steps
Operating flow
- Step 01
Ingestion
Ingest documents, policies, FAQs, and data.
- Step 02
Ontology Mapping
Map terms, entities, and relations onto the schema.
- Step 03
Validation Gate
Three-stage review of extraction accuracy and relation conflicts.
- Step 04
Hybrid Serving
Vector+Graph retrieval supplies the basis for answers.
- Step 05
Operation Loop
Monitor wrong answers and semantic drift; update knowledge.
— Operating Principles
Reliability that regulated industries and enterprise AI need
Explainability
Show the basis document and graph path for every answer.
Cost Optimization
Cut duplicate knowledge; optimize the hot-path search.
Governance
Manage owners, approvers, and change history.
SaaS Expansion
Commercializable as internal knowledge assistants and customer-support QA.
Other R&D
Back to CRAX →- R&D · 01
Multimodal Story-verse Creation Platform
Creation as a verifiable collaboration structure, not a single generation.
- R&D · 02
Conversational Multimodal AI for Media Production
Conversation becomes a production brief; the brief becomes an editable timeline.
- R&D · 04
Urban Data Platform × Edge AI Integration
On-site readings of urban change loop back as urban services.