Insights
Insights
Field notes on agentic AI, enterprise PMO delivery, and turning approved budget into measured value.
Insights
Enterprise AI Value: Insights from my recent trip to Toronto
Between September 20 and 25, I was in Toronto, invited by TBDC, together with 17 other European startups. ODYX was the only Greek company in the group. I also attended NRTH Festival 2026, where I had the chance to exchange views with founders, VCs, enterprises and people building in the AI ecosystem. Different conversations, but […]
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Insights
How Do You Know If Your IT Project Requirements Are Actually Good Enough?
I have seen many requirements documents over the years. Some were 100 pages long and still left major questions unanswered. Others were much shorter, but clear enough for a delivery team to understand what needed to be built and for a vendor to prepare a meaningful proposal. So, for me, the real question is not: […]
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Insights
Governance-first AI: enterprise AI must understand governance, not just generate text
For decisions that must be defensible, the capacity to generate text is the least interesting thing an AI can offer. What matters is whether the system understands the governance it operates within.
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Insights
Should we do it, and can we deliver it? Aligning business value with delivery reality before approval
Every enterprise investment is two questions wearing one coat: is it worth doing, and can we deliver it responsibly? Answering them separately is where wasted investment begins.
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Insights
The demand-stage gap: why enterprise projects fail before they start
When a project fails, the inquest looks at delivery. But a large share of those failures were decided long before any code was written — at the demand stage, when a vague request was accepted as a clear one.
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Insights
Engineering trustworthy AI workflows: turning a conversation into a governed business case
A model will happily draft a confident business case. The engineering that matters is everything that happens after it stops talking — standardised prompts, validation and a trail you can defend.
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Insights
From idea to review-ready evidence: why we built Fungy.ai as a discovery layer
Most enterprise AI starts at generation. We started at discovery — because projects are won or lost upstream, in the stretch between a request and something delivery can act on.
Start with one real demand.
We start with a focused discovery session and a short demonstration using one of your real demands.