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Knowledge Governance

9 articles · Page 1 of 1
DataFunSummit
DataFunSummit
Sep 4, 2026 · Artificial Intelligence

Ontology-Driven Knowledge Engineering: Building Trustworthy Enterprise AI Agents Beyond RAG

This article details an ontology-driven three-layer architecture for enterprise office agents, replacing standard RAG with GraphRAG to achieve verifiable, auditable AI. It covers a six-step modeling method, a six-dimensional evaluation system, a two-week MVO rollout, and three production scenarios — document review, meeting minutes, and document structuring — showing how semantic assets become the true competitive moat.

GraphRAGKnowledge GovernanceMVO
0 likes · 37 min read
Ontology-Driven Knowledge Engineering: Building Trustworthy Enterprise AI Agents Beyond RAG
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 3, 2026 · Industry Insights

OntoL: Ontology Modeling & Semantic Layer for Enterprise Knowledge Governance

This article analyzes OntoL, an ontology modeling tool for enterprise knowledge governance, detailing its three-layer architecture, core capabilities like visual modeling and versioning, applicable scenarios, current technical limitations, and future roadmap including SHACL constraints and federated query.

Data IntegrationKnowledge GovernanceOWL
0 likes · 9 min read
OntoL: Ontology Modeling & Semantic Layer for Enterprise Knowledge Governance
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Aug 29, 2026 · Industry Insights

How to Lightly Deploy Ontology in Enterprises: Three Practical Scenarios

The article diagnoses three core data‑knowledge pain points in enterprise digital transformation, proposes five ontology‑driven principles and a three‑layer mapping architecture, and illustrates lightweight, iterative rollout through three concrete scenarios covering design‑as‑modeling, enterprise‑wide semantic governance, and executable ontology for AI agents.

AI IntegrationEnterprise DataKnowledge Governance
0 likes · 16 min read
How to Lightly Deploy Ontology in Enterprises: Three Practical Scenarios
Ray's Galactic Tech
Ray's Galactic Tech
Jul 17, 2026 · Artificial Intelligence

High‑Concurrency RAG: When to Use Classic, Graph or Agentic Architecture

The article analyzes why production‑grade RAG systems fail under load and explains how Classic, Graph, and Agentic RAG each address specific problem stages, offering concrete engineering guidelines for query normalization, caching, versioned knowledge, graph construction, stateful agents, and governance to achieve stable high‑throughput performance.

Agentic RAGCachingHigh Concurrency
0 likes · 31 min read
High‑Concurrency RAG: When to Use Classic, Graph or Agentic Architecture
Frontline Investigation
Frontline Investigation
Jun 30, 2026 · Industry Insights

Why Enterprise AI Q&A Fails: Knowledge Governance, Not Model Quality

This article argues that unreliable enterprise AI Q&A systems stem from poor knowledge governance — not model limitations — and outlines five essential questions a trustworthy knowledge base must answer: source traceability, version validity, applicability scope, ownership, and error correction loops.

AI Knowledge BaseEnterprise AIISO 42001
0 likes · 15 min read
Why Enterprise AI Q&A Fails: Knowledge Governance, Not Model Quality
DataFunTalk
DataFunTalk
Jun 26, 2026 · Industry Insights

Ontology Is a Management Challenge, Not a Technical One – Enterprise AI Insights

In a 90‑minute roundtable, industry veterans from Huawei, Ping An and a startup dissect why ontology is a governance issue rather than a technical hurdle, expose the paradox of modeling pain, describe two common AI‑adoption ailments, warn of hidden technical debt in highlight projects and share hard‑won lessons on building AI‑native organizations from the ground up.

AI transformationAI-Native OrganizationEnterprise AI
0 likes · 17 min read
Ontology Is a Management Challenge, Not a Technical One – Enterprise AI Insights
DataFunSummit
DataFunSummit
Jun 24, 2026 · Artificial Intelligence

Why Ontology Is No Longer a Technical Issue – Exploring Enterprise AI’s Non‑Technical Challenges

In a 90‑minute round‑table, industry experts dissect how ontology has become a management problem, reveal the paradox of AI modeling, expose hidden technical debt in flashy projects, and argue that true AI transformation demands organizational change rather than merely swapping technologies.

AI transformationAI-Native OrganizationEnterprise AI
0 likes · 16 min read
Why Ontology Is No Longer a Technical Issue – Exploring Enterprise AI’s Non‑Technical Challenges
Frontline Investigation
Frontline Investigation
Jun 23, 2026 · Industry Insights

Government AI Assistants: From Answering to Controlled Collaboration

This article analyzes how government AI assistants are evolving from simple Q&A tools into controlled process collaborators, examining the layered capabilities required, the critical need for authoritative knowledge governance, risks of formalism, and why the future lies in 'controlled collaboration' agents that reduce friction without replacing human judgment.

AI GovernanceControlled CollaborationDigital Government
0 likes · 17 min read
Government AI Assistants: From Answering to Controlled Collaboration
AntTech
AntTech
Oct 28, 2024 · Artificial Intelligence

Highlights of AI Large‑Model Sessions at CNCC 2024

The CNCC 2024 conference featured a series of expert talks on AI large‑model research, covering paradigm shifts in scientific discovery, knowledge enhancement and governance, data‑infrastructure analytics, vertical‑domain inference, diffusion‑model advances, multimodal model progress, and medical AI applications, illustrating the breadth and impact of large‑model technologies across multiple domains.

AIKnowledge GovernanceMultimodal
0 likes · 9 min read
Highlights of AI Large‑Model Sessions at CNCC 2024