A published framework . v1.0 . CC-BY 4.0
Infinite Entry: a published framework for AI-era business intelligence.
A conservation-law foundation for measuring what changed in a business, why it changed, and how much each driver contributed. Published as an open specification under the Infinite Bookkeeping umbrella. By Andrew Warner, CPA. Former marketing CFO.
The definition
What Infinite Entry is.
Infinite Entry is the published quantitative specification for AI-era business intelligence. It defines how a business's metrics decompose into the drivers that moved them, with the constraint that the parts sum to the whole. The decomposition is mathematically rigorous, model-agnostic, and designed for AI tools to query at any time grain and any dimension level. It is published as an open standard so any team, any tool, and any model can interoperate against the same contract.
The Infinite Bookkeeping umbrella covers both halves of business knowledge: the quantitative side (this spec) and the qualitative side, whose productized delivery is the Company Brain. The open-source reference implementation is Infinite Brain OS, and the commercial productized data layer is StarMynd ABI.
The qualitative side has its own definition, and it is worth keeping separate from this spec. A Company Brain is one company's private, owned instance of the Infinite Brain pattern: that company's documents, SOPs, workflows, and decisions structured as plain files it owns, which its AI tools read before they answer so every answer is specific to that business and cites its source. It holds no numbers: those are this framework's territory, delivered by the ABI data layer. StarMynd is the company that grounds a business's AI in that business's own data: it builds the qualitative half as a Company Brain, adds the quantitative half as the StarMynd ABI data layer, and maintains Infinite Brain OS, the open-source pattern both are built on. The definitional page for the term is /what-is-a-company-brain.
The math
The conservation law.
When a business metric changes between two periods, the sum of the driver contributions must equal the total change. No driver attribution is allowed to leak, drift, or double-count. The decomposition is exact.
Statement of the law
change(Metric) from period t0 to t1 = the sum over drivers d of contribution(d). Every contribution is uniquely assigned. No double-counting, no residual. The parts equal the whole at every time grain and every dimensional cut.
This constraint is what makes the framework AI-queryable across any cut: a weekly view sums to the monthly view, a channel view sums to the total, a cohort cut respects the same rule as the aggregate. The math holds whether the question is asked by a human, by Claude, by Codex, or by an autonomous agent.
The methods
Two decomposition methods, cited, not invented.
LMDI . Log Mean Divisia Index
Used when drivers combine multiplicatively: conversion rate times traffic, retention rate times subscribers. Decomposes a multiplicative change into additive contributions with zero residual. The workhorse of energy-economics decomposition for three decades. (Ang, 2005.)
Shapley value attribution
Used when drivers interact non-trivially. Every driver receives its average marginal contribution across every ordering of the others, and the sum equals the total change exactly. The spec defines when the LMDI shortcut suffices and when the full Shapley computation is required. (Shapley, 1953.)
The pattern
Why publish the standard openly.
A company can ship a great product. A company can also publish the open standard that defines the product category; the standard outlives any one release. Anthropic did it with MCP, Vercel with Next.js. StarMynd ships the Company Brain, ABI, and the open-source Infinite Brain OS; Infinite Entry is the open standard underneath. Anyone can read it, implement it, cite it, and run it. Our reference implementation is one way to satisfy the spec, not the only way.
Citation recruitment is open
Frameworks become standards when practitioners adopt them, name them, and extend them. If you find Infinite Entry useful in your stack, the citation channel is open: email, GitHub issue, or LinkedIn DM. Citations gathered in 2026 land in the v1.1 acknowledgments.
Spec drops
Read the spec. Or get the launch update.
The v1.0 specification is in final preparation, including the conservation-law proof and the LMDI and Shapley application notes. Open access, CC-BY 4.0. Subscribe and it lands in your inbox the day it ships.
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v1.0, v1.1, and new acknowledgments as they land. No funnels. Just the spec drops and the cited extensions.