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AI Documentary Quality-Control Template
Ready for a real production.

A final-cut review scorecard covering story, facts, reconstruction, continuity, audio, rights, disclosure, and publication readiness.

Runtime
Final review artifact
Format
Pass, repair, or reject scorecard
Audience
Creators, producers, agency reviewers, and channel owners

Use this brief

Review the exact exported film [file/version] against the approved brief. Score story clarity, evidence, narration, visual accuracy, continuity, artifacts, music, captions, rights, disclosure, and channel fit. Record timestamped issues and make an explicit pass, repair, or reject decision.

Required inputs

  • Exact final export and version identifier
  • Approved brief, research pack, claim ledger, and screenplay
  • Target audience, channel standard, rights notes, and disclosure policy
  • A reviewer who did not make every production decision

Editorial structure

  1. 1

    First watch: judge comprehension, trust, pacing, emotion, and willingness to publish without pausing.

  2. 2

    Evidence pass: verify every material claim, quote, date, number, and uncertainty label.

  3. 3

    Visual pass: inspect reconstruction accuracy, continuity, anatomy, physics, text, and artifacts.

  4. 4

    Audio pass: check pronunciation, intelligibility, pauses, music balance, clipping, and caption alignment.

  5. 5

    Release pass: clear rights, disclosure, title, thumbnail, description, sources, and the exact exported file.

Acceptance checks

  • Record issues with timestamps, severity, owner, and acceptance condition.
  • Do not approve because individual shots look cinematic; judge the complete film.
  • Rewatch repaired sections in context and then watch the final export end to end.
  • Keep the review record with the published version and source notes.

Visual direction

Quality means legible storytelling and credible subject detail, not maximum spectacle in every shot.

Narration direction

The final voice must sound intentional, pronounce key terms correctly, and preserve the approved certainty level.

Evidence and next steps

Complete Onira Studio films are first-party product evidence, not customer case studies or guarantees of factual accuracy, publication acceptance, retention, or revenue.

Questions

What is the right success metric for an AI documentary tool?

For production decisions, measure time and effective cost per accepted film, including human corrections, failed generations, external tools, and rejected outputs.

Should the same person generate and approve the film?

A second reviewer is valuable for factual trust, comprehension, artifacts, and rights because the operator can become blind to issues after repeated revisions.