AI video archives answer questions that appear after publication: Who approved this shot? What source was used? Which claim was removed? Where is the uncropped master?
A complete archive preserves decisions and context, not just the final compressed file.
Core artifacts
Archive the production brief, storyboard, continuity map, shot list, shot contracts, source references, prompt history, model or tool versions, generations, rejected examples, and review decisions.
Include the editing project or equivalent decision record, voiceover script, pronunciation lexicon, audio files, captions, transcript, thumbnails, and all platform exports.
Rights and consent
Record ownership and license scope for source footage, images, music, fonts, voices, likenesses, and generated assets. Note expiration, territory, channel, and revocation conditions.
If provenance credentials are present, archive them with a plain-language note about what they establish and what remains outside the credential.
Approval and claims history
Keep the final claims audit, reviewer identities, qualification decisions, disclosure decision, and the reasons major shots were accepted or rejected.
When a future editor changes one sentence or clip, this record shows which earlier conclusions must be revisited.
Retention and retrieval
Define retention by legal, brand, platform, and reuse needs. Store assets with stable IDs and checksums where integrity matters.
Test retrieval annually or after a major workflow change. An archive that cannot be opened or interpreted is not operational.
Conclusion
Archive the production decision, not merely the published pixels. Stable IDs, rights context, approvals, captions, and masters make future reuse safer.
Editorial note: This guide was drafted with AI assistance, then checked and edited against the sources listed below on September 20, 2026. It does not report an unperformed product test.
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