Notes on enterprise knowledge & semantic AI
How teams connect their tools, find what they already know, and put a semantic layer to work, written plainly and grounded in real sources.
Knowledge Graphs··7 minSemantic Layers: The Catalog Owner Playbook
The semantic layers catalog owner data leader playbook: who owns shared business vocabulary, how to govern it, and a 90-day rollout plan.
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Future of Work··7 minEverything Recorded: Capturing Enterprise Tacit Knowledge
How everything-recorded enterprise tacit knowledge capture by default turns conversations into a living context layer that AI agents can reason over.
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Product & Company··6 minDatabricks Unity Catalog: A Universal Semantic Layer
The Databricks Unity Catalog universal semantic layer makes metrics first-class assets, signaling catalogs are becoming the governance core for AI.
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Enterprise AI··7 minAI Transformation Predictions 2026: Don't Weaponize Inefficiency
AI transformation predictions for 2026 weaponize inefficiency when bolted onto broken processes. The fix: a unified semantic layer plus audited autonomy.
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Enterprise AI··6 minAI Spending Forecasts 2026: Gartner, IDC, Stanford
AI spending forecasts 2026 from Gartner, IDC, and Stanford measure three different things. Here is what each number counts and how to cite it correctly.
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Industry Use Cases··7 minUNIQA Insurance AI Assistant Case Study
The UNIQA Insurance enterprise AI assistant case study shows how an AI brain over fragmented compliance docs reclaimed 30-40% of staff search time.
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Future of Work··6 minTurnover: The Hidden Threat to Institutional Knowledge
Employee turnover institutional knowledge loss is a continuity threat, not just a hiring cost. Here is what walks out the door and how to keep it.
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Product & Company··6 minServiceNow Otto: One Permission-Aware AI Layer
The ServiceNow Otto unified AI experience control tower shows why enterprises want one permission-aware conversational layer, not isolated AI inside each app.
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Knowledge Graphs··6 minOntology-Grounded Reasoning for Snowflake Cortex Agents
Ontology grounded reasoning in Snowflake Cortex agents lifted benchmark accuracy from 50% to 78%. Here's why typed relationships beat raw schemas.
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Knowledge Graphs··6 minNeo4j NODES 2025 Recap: Graph + GenAI in Production
A Neo4j NODES 2025 recap of graph GenAI use cases: how GraphRAG, knowledge graphs, and agent memory moved from prototypes into production systems.
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Knowledge Graphs··6 minKnowledge Graph 230% ROI: The IDC Neo4j Study
The knowledge graph 230 percent ROI IDC Neo4j study gives CFOs hard numbers: $4M annual benefit, sub-8-month payback, and 44% fewer AI hallucinations.
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Knowledge Management··6 minThe Knowledge Delivery Problem: Why Teams Re-Research
The enterprise knowledge delivery problem and re-research silos waste hours: good intelligence exists but never reaches the decision. Here is the fix.
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