Blog
Notes from the build.
Field notes on building AI-native companies for regulated industries, deployment, data loops, and the numbers that move.
What Is an AI Venture Studio? The Co-Founding Model, Explained
Incubators mentor. Accelerators batch. VCs write cheques. A venture studio co-founds, and for AI companies, that difference is structural.
Venture Studios in London: A Founder's Guide for 2026
London has more venture studios than any city in Europe, and they are not interchangeable. How the model works, the questions that separate builders from advisers, and how to choose.
Cutting False Positives in Financial Crime Detection with Adaptive AI
Rule-based transaction monitoring buries compliance teams in alerts that go nowhere. The fix isn't better rules, it's a system that learns from every alert an analyst clears.
AI Accounting Automation: What Small Businesses Can Hand Over in 2026
Bookkeeping is the classic evenings-and-weekends tax on small business owners. Here's what genuinely automates in 2026, and the design principle that makes it safe.
Deploying AI in Regulated Industries: The Gap Between a Demo and a Business
Model capability keeps doubling; enterprise adoption doesn't. The distance between them is engineering, and in regulated markets, that distance is the entire prize.
Forward-Deployed Engineers: Why AI Products Are Built Inside the Customer
The best applied-AI teams don't ship software to their customers, they ship engineers. Here's why the forward-deployed model wins, and what it takes to run it well.
Intelligent Document Processing: From OCR to Answers
OCR digitised documents; it didn't understand them. Modern document processing is a pipeline with checkpoints, and the endgame isn't extraction, it's search that answers questions.
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