Launching the TrancheBook blog
Why we publish — and what the monthly cadence will cover: ranking commentary, sectoral takes, anonymized IC memo case studies, and calibration retrospectives.
TrancheBook is a research platform for institutional capital allocators in private AI. Our two products — IC memos and the company ranking — are built on a deterministic verification stack: kill gates, calibration tracking, source provenance, and a Chinese Wall between the ranking engine and broker fee economics. The methodology page documents the stack in detail.
The blog exists to make that stack legible. Methodology is words; the receipts are calibration retrospectives, sector deep-dives, and case studies of memos that landed (or didn’t). We publish monthly. The cadence is intentional — quarterly is too sparse to be a feedback loop, weekly is a content treadmill that drifts away from rigor.
What you should expect to see here: ranking commentary the week after the public top-10 refresh; a sectoral take roughly once a quarter on a slice of the AI universe (foundation models, infrastructure, vertical AI, application layer); an anonymized IC memo case study when a customer gives permission; and calibration retrospectives — published whether or not the news is good for us — when prediction horizons resolve.
The platform is not done. The blog will follow what the product surfaces, not the other way around. If you’re an accredited investor who wants the underlying surfaces, request access. If you want to subscribe to the monthly digest, the form on the homepage drops you on the list.