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Ontology Intelligence

5 articles · Page 1 of 1
Data Bricklaying Diary
Data Bricklaying Diary
Sep 15, 2026 · R&D Management

Evaluating Ontology Intelligence Projects: 6 Dimensions Beyond Concept Counts

This article argues that ontology intelligence projects must be evaluated on end-to-end business outcomes rather than concept or triple counts, proposing a six-dimension framework—business value, semantic quality, decision reliability, action closure, security governance, and unit economics—with mandatory safety thresholds and phase-gated decisions to expand, optimize, restrict, or stop projects.

KnowledgeOpsOntology Intelligenceaction reliability
0 likes · 37 min read
Evaluating Ontology Intelligence Projects: 6 Dimensions Beyond Concept Counts
Data Bricklaying Diary
Data Bricklaying Diary
Aug 18, 2026 · Artificial Intelligence

Semantic Models ≠ Live State: Why Agents Need Object Runtime

This article distinguishes semantic models (which define business object meanings) from object runtime (which provides traceable, versioned projections of specific object states for AI agents), detailing five core responsibilities, differences from data platforms and agent runtimes, a credit-adjustment case study, and guidance on when and how to implement minimal object projections.

Agent ArchitectureCDCMCP
0 likes · 21 min read
Semantic Models ≠ Live State: Why Agents Need Object Runtime
Data Bricklaying Diary
Data Bricklaying Diary
Aug 11, 2026 · Artificial Intelligence

Three-Layer Ontology Intelligence: Separating Semantics, Decisions, and Actions

This article explains why ontology intelligence systems require a three-layer architecture—semantic layer for defining business meaning, decision layer for forming explainable action plans, and action layer for controlled state changes—with explicit handoff contracts to avoid mixing rules and side effects into prompts.

AI architectureDecision LayerOntology Intelligence
0 likes · 20 min read
Three-Layer Ontology Intelligence: Separating Semantics, Decisions, and Actions
Data Bricklaying Diary
Data Bricklaying Diary
Aug 6, 2026 · Artificial Intelligence

From Ontology Semantics to Ontology Intelligence: Why Understanding Business ≠ Driving It

The article distinguishes ontology semantics (AI understanding business objects, states, rules) from ontology intelligence (explainable decisions, contract-constrained actions, auditable loops), outlining seven engineering capabilities needed to close the loop and emphasizing a minimal viable loop around high-value decisions.

Action ContractsAgent ArchitectureAgent Runtime
0 likes · 16 min read
From Ontology Semantics to Ontology Intelligence: Why Understanding Business ≠ Driving It
Data Bricklaying Diary
Data Bricklaying Diary
Aug 5, 2026 · Industry Insights

Ontology Intelligence: Closing the Engineering Gap for Enterprise AI Agents

This article introduces the Ontology Intelligence series, explaining why enterprise AI agents fail in production without unified business semantics, current object state, explainable decisions, controlled actions, and continuous governance—outlining a five-layer framework and scenario-based criteria for adopting ontology-driven architectures.

AI Production GapAgent ArchitectureControlled Actions
0 likes · 18 min read
Ontology Intelligence: Closing the Engineering Gap for Enterprise AI Agents