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Your trusted resource for the latest ideas, concepts and news surrounding enterprise-AI decision intelligence.

Who Should Own Your Enterprise Context Layer?

AI accuracy doesn't come from the model. It comes from the business context behind it. That context is your IP, so keep it behind your firewall, standards based and independent of every vendor that wants to hold it for you.

October 4, 2026

Build vs. Buy an Enterprise Context Layer: The Real Tradeoffs

August 5, 2026

The Modern Data Stack Is Missing a Layer: Where Semantic Layers, Context Layers, and Knowledge Graphs Fit in

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Technology

The Modern Data Stack Is Missing a Layer: Where Semantic Layers, Context Layers, and Knowledge Graphs Fit in

July 11, 2026

The Context Layer: Why Answering a "Simple" Business Question Is So Hard for LLMs

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The Context Layer: Why Answering a "Simple" Business Question Is So Hard for LLMs

June 11, 2026

Beyond Dashboards: How Model-Driven Intelligence Turns Enterprise Data into Decisions

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Beyond Dashboards: How Model-Driven Intelligence Turns Enterprise Data into Decisions

May 5, 2026

Why Your AI Data Scientist Doesn't Understand Cause and Effect—And Why That Matters

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Technology

Why Your AI Data Scientist Doesn't Understand Cause and Effect—And Why That Matters

April 28, 2026

From Hive to Harvest: AI and the Mighty Honey Bee

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From Hive to Harvest: AI and the Mighty Honey Bee

April 22, 2026

How I Prototyped a Utility Issue Alerting App in Under an Hour

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How I Prototyped a Utility Issue Alerting App in Under an Hour

April 15, 2026

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Part 2: From Proof of Concept to Production — The AI Delivery Playbook

March 25, 2026

Platform

Part 1: Escaping “Pilot Purgatory” — Why AI Proof of Concepts Fail

March 25, 2026

App Orchid Enables Role-based Control of LLMs in Agentic BI

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App Orchid Enables Role-based Control of LLMs in Agentic BI

March 18, 2026

AI Guardrails: How a Governed Semantic Layer Keeps AI Accurate and Trusted

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Technology

AI Guardrails: How a Governed Semantic Layer Keeps AI Accurate and Trusted

March 18, 2026

Advancing Enterprise AI Governance and Decision Intelligence

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Advancing Enterprise AI Governance and Decision Intelligence

March 18, 2026

A version of a16z’s Modern Context Layer vision: The App Orchid Approach

Technology

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A version of a16z’s Modern Context Layer vision: The App Orchid Approach

March 11, 2026

“Why Can’t I Just Do This in Microsoft Fabric?”

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“Why Can’t I Just Do This in Microsoft Fabric?”

February 11, 2026

Automated Ontology Discovery: How App Orchid Reduces Manual Data Modeling

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Platform

Automated Ontology Discovery: How App Orchid Reduces Manual Data Modeling

February 1, 2026

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Who Should Own Your Enterprise Context Layer?

Build vs. Buy an Enterprise Context Layer: The Real Tradeoffs

The Modern Data Stack Is Missing a Layer: Where Semantic Layers, Context Layers, and Knowledge Graphs Fit in

The Context Layer: Why Answering a "Simple" Business Question Is So Hard for LLMs

Beyond Dashboards: How Model-Driven Intelligence Turns Enterprise Data into Decisions

Why Your AI Data Scientist Doesn't Understand Cause and Effect—And Why That Matters

From Hive to Harvest: AI and the Mighty Honey Bee

How I Prototyped a Utility Issue Alerting App in Under an Hour

Part 2: From Proof of Concept to Production — The AI Delivery Playbook

Part 1: Escaping “Pilot Purgatory” — Why AI Proof of Concepts Fail

App Orchid Enables Role-based Control of LLMs in Agentic BI

AI Guardrails: How a Governed Semantic Layer Keeps AI Accurate and Trusted

Advancing Enterprise AI Governance and Decision Intelligence

A version of a16z’s Modern Context Layer vision: The App Orchid Approach

“Why Can’t I Just Do This in Microsoft Fabric?”

Automated Ontology Discovery: How App Orchid Reduces Manual Data Modeling

The Best Path to AI-Ready Data

The Best Path to
AI-Ready Data