How we think
When Software Gets Cheap, Your Data Becomes the Moat
When Software Gets Cheap, Your Data Becomes the Moat
When anyone can build software with AI, proprietary data becomes the moat. Here’s what a real data moat looks like, and three moves to start building yours.
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If AI Writes Code, Who Tests It?
If AI Writes Code, Who Tests It?
AI can write working code in seconds. The harder question is who makes sure it is right for the customer, the business and the risk you are willing to accept. A QE leader on why quality engineering has to move upstream.
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Enterprise Search That Cites Its Sources: How It Works
Enterprise Search That Cites Its Sources: How It Works
AI enterprise search that cites its sources links every answer to the passage behind it. Here is how the seven-step pipeline works, where it goes wrong and how to measure it before go-live.
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Why Agentic AI Deals Stall Between the Demo and the Statement of Work
Why Agentic AI Deals Stall Between the Demo and the Statement of Work
Agentic AI pilots rarely fail on technology. They stall because the business case was never documented, governance arrived late and the champion was left to sell it alone. Here is how to sequence the next pilot so it reaches production.
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Document AI in 2026: From Messy Documents to AI-Ready Data
Document AI in 2026: From Messy Documents to AI-Ready Data
Document AI turns PDFs, scans and emails into AI-ready data. See how intelligent document processing works in 2026, plus a 90-day roadmap to production.
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Mid-Market AI: The Enterprise Playbook Doesn’t Scale Down
Mid-Market AI: The Enterprise Playbook Doesn’t Scale Down
Why the enterprise AI playbook fails at mid-market companies, and what works instead: AI that runs on imperfect data, needs no dedicated team, has governance built in and pays back within a quarter or two.
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AI Use Case Prioritisation: A Scoring Framework
AI Use Case Prioritisation: A Scoring Framework
A practical, weighted scoring framework to prioritise AI use cases by value, feasibility, risk, cost, time to value and strategic fit, with a worked example and a value-feasibility matrix.
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Copilot vs Agent vs Assistant: Terminology That Matters
Copilot vs Agent vs Assistant: Terminology That Matters
Copilot vs agent vs assistant: how the three differ on autonomy, cost and risk, plus a one-question test for what a vendor is really selling.
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Global Company of the Year for Digital CX
Global Company of the Year for Digital CX
Frost & Sullivan named Compunnel its 2026 Global Company of the Year for digital customer experience. Download the free 11-page report on AI-driven CX.
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What Is Agentic AI? A Practical Definition for Enterprise Teams
What Is Agentic AI? A Practical Definition for Enterprise Teams
Agentic AI is software that takes a goal, plans its own steps and acts on real systems. Learn how it differs from AI agents and RPA, and where it pays off.
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Enterprise RAG Explained: Architecture, Costs and Failure Modes
Enterprise RAG Explained: Architecture, Costs and Failure Modes
Enterprise RAG explained: how the architecture works stage by stage, what it really costs, the 7 failure modes that break retrieval, and what to test before you build or buy.
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What Is Enterprise AI? The Answer Is Not the Technology
What Is Enterprise AI? The Answer Is Not the Technology
Nine in ten large companies run AI somewhere, but only 6% see it move earnings. What enterprise AI is made of, why it stalls, and what the 6% do right.
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