RecitID

Editorial standards

Our scholarly methodology

Last updated

RecitID identifies recitations and surfaces tafsir written by classical and contemporary scholars. We do not issue fatwas, we do not author religious rulings, and we do not paraphrase scripture. Every passage we display is verified against canonical Mushaf text.

What we do

RecitID is an identification and study aid. We answer three questions: which surah, which ayah range, and which qari is reciting. The Quranic text we display is the Uthmani Mushaf, character-for-character.

What we never do

We never issue rulings (fatwa). We never paraphrase the Quran in our own words. We never AI-generate Arabic Quranic text. We do not rank reciters or qira'at by religious merit — only by acoustic match confidence.

Verification chain

Each verse displayed is loaded from a verified Uthmani Mushaf source and cross-checked against the Tanzil text corpus before render. If a verse fails verification, we suppress it and surface the surah/ayah numbers only.

  • Mushaf source: Uthmani script (Madinah print).
  • Cross-check: Tanzil project (verified plain-text corpus).
  • Diacritics preserved exactly; no normalization applied to displayed Quranic text.

Tafsir attribution

Every tafsir excerpt is attributed by name to its author and source work (e.g., Tafsir Ibn Kathir, Tafsir al-Saadi). AI summaries of tafsir are clearly marked and link to the unmodified source.

Frequently asked

Does RecitID issue religious rulings?

No. RecitID is an identification and study tool. For rulings (fatwa), consult a qualified scholar in your madhhab. We surface scholarly opinions with full attribution; we do not author them.

Is the Quranic text in RecitID authentic?

Yes. Every ayah we display is loaded from a verified Uthmani Mushaf and cross-checked against the Tanzil corpus before render. We never AI-generate or paraphrase Quranic text.

Why don't you rank reciters by skill?

Recitation quality is judged by qualified ijaza-holders, not by an app. Our ranking is purely acoustic — how confident our model is that a given audio sample matches a given qari's known recordings.

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