Most enterprise AI failures begin before the model ever sees the data. A real Hindi government letter, two AI systems, one handwritten reference number — and the difference between retrieval quality and model sophistication.
AI will eliminate most reading in due diligence. It will not eliminate judgment. That’s the asymmetry every deal team needs to think about. I’ve spent over twenty years on the buy side â residential, commercial, affordable housing, stressed assets, slum…
63% of Indian AI startups pivoted their core model in the past 12 months. The wrappers are dead. Here's the PE diligence framework that tells you what's left worth investing in — and the one diligence question that every AI deal needs in 2026.
Most enterprise AI systems would fail a basic audit — and that is the real reason they will never scale. Why audit trails are the missing layer between an AI pilot and a production system, and why the people best equipped to design them are not engineers but financial controllers, compliance officers, and chartered accountants.
I am a chartered accountant. I also compile my own operating system from source code and run AI models on an integrated GPU with no dedicated memory. These two facts are not unrelated. When I write about enterprise AI strategy…
The AI industry has spent billions trying to solve hallucination. The wrong profession has been doing it. Here’s the contradiction nobody talks about: the problem of confident, coherent, wrong output — a system that fabricates answers indistinguishably from correct ones…
The build vs buy decision for enterprise AI isn't a technology question — it's an investment question. A PE framework for evaluating total cost of ownership, data sovereignty, competitive moats, and exit optionality.
My wife’s laptop crashed one evening. No warning, no recovery option. Years of photos, documents, and personal files — gone in an instant. What I built in response — a home lab running 30+ containers — ended up teaching me…
Most enterprise AI conversations begin with the same question: which model should we use? This is the wrong starting point. In production systems the model is often the smallest component of the architecture. The real work lies in the layers…
Most organisations are trying to deploy AI into systems that were never designed to accommodate uncertainty. Over the past two years most organisations have launched AI pilots. Very few have deployed AI systems at scale. This gap is often explained…