Editorial Guidelines

All numerology content on this site is based on the Pythagorean system, the most widely used method in the world. It is called "Pythagorean" because it draws on later Pythagorean ideas about number and harmony (Pythagoras, c. 570–495 BCE, left no writings of his own); the familiar A–Z chart assigning letters values 1 to 9 is a modern system, standardized in the early 1900s.

We also offer two alternative systems: Chaldean numerology from ancient Babylon and Kabbalistic numerology rooted in Hebrew Gematria. Each system is clearly labeled so you always know which method is being used.

We distinguish between kinds of sources and what each can support. For historical claims — where a system came from, who wrote what, and when — we rely on academic references (for example, the Stanford Encyclopedia of Philosophy for Pythagoras) and recognised treatments of primary texts. Practitioner literature documents what modern numerologists teach and practise, but we do not treat it as evidence about antiquity.

We do not invent meanings: number interpretations reflect descriptions found across established numerology literature, and where schools disagree we say so. Per-article bibliographies are being added across the Learn library — starting with the history-bearing essays — and appear at the end of each article as they land.

The English reference content on this site — interpretations, guides, and calculator explanations — is written and reviewed by people. Three things do use AI, and we label them: optional personalised PDF reports use AI running on our own hardware to adapt our editorial interpretations to your chart; translations into languages other than English are machine-generated from the human-written English source and reviewed with dedicated tooling; and some Journal posts are AI-drafted from our editorial framework before human review. AI is never used to invent numerological meanings — the editorial source of truth is human-written.

The calculations themselves are deterministic math — the same inputs always produce the same outputs. You can verify any result by following the step-by-step breakdown shown with each calculation.

Learn articles are researched, written, and maintained by Diogo Lemos, the creator of Esoteric Numbers. Every article carries a visible byline with its author and dates — the same attribution our structured data reports.

We do not use fictitious authors, personas, or invented credentials. When outside contributors take part — for example native-language review or cultural review of a tradition article — they are credited by name on the articles they reviewed.

English is the source language: all reference content is written and reviewed in English first. Other languages are machine-translated from that source, protected by a curated glossary, and checked with dedicated audit tooling; passages without a translation yet fall back to English rather than showing a broken page.

We only present a language to search engines as fully supported once its translation passes a completeness threshold, and human review of a sample precedes any such promotion. If you spot a translation error, report it through the contact page — human corrections are protected from being overwritten by later automated runs.

How a claim gets checked before it ships: historical statements are verified against the academic references described above and rewritten as attributed interpretation when they cannot be; calculations are covered by automated tests that recompute the published examples; and counts shown on the site are derived from the same data that builds it, so they cannot drift from reality. Every Learn article carries a visible last-reviewed date, and each article receives a substantive review at least once a year — sooner when a reader report or a source change touches it.

Conflicts of interest: this site currently carries no affiliate links, no sponsored content, and no paid placements — revenue comes only from the clearly-labelled personalised reports. If that ever changes, the affected pages will carry a disclosure at the point of recommendation, and this policy will be updated first.

We review and update our content regularly. If you find an error or have a suggestion, please contact us through our contact page. We take accuracy seriously and will correct verified issues promptly.

Every Learn article shows a visible byline with its author, publication date, and the date of its last substantive review — the same values our structured data reports, so they can never drift apart. Substantive corrections are noted in the affected article.