Pre-publish readiness gate for AI avatar video

Scale avatar video.Ship each one clear to publish.

AI avatars make talking-head video cheap to produce — and easy to get wrong on consent and truthfulness. This system checks every video on both, and returns a verdict — READY / FIX / BLOCK — plus one library gate before the set goes out.

Get the System — $89one-time · instant download · yours to keep

Not legal advice. This is triage and documentation support. Platform consent requirements, state likeness law, and the EU AI Act Article 50 date move quickly; verify against primary sources and have counsel review anything high-stakes.

Five deliverables · runnable
Readiness Checker
Python
Same logic as a workbook
Excel / Sheets
Consent & Disclosure Workflow
Playbook
Script-to-Avatar Production SOP
Playbook
Sample Video Set
8 videos
Works alongside
Voice & Likeness Gate · AI Literacy Kit · Short-Form Video System
01.The Problem

The avatar is easy. The clearance is the work.

A custom avatar of a real person needs that person’s consent on file. An avatar can’t claim it used your product. A dubbed version can drift in meaning. None of these stop the render — but each one stops a clean publish.

Consent

A custom avatar of a real person needs a completed consent artifact — 'pending' doesn't clear it.

0

Lived experiences an avatar has. So it can't give a first-person testimonial, no matter how polished.

Per dub

Every localized version needs its own QA pass — meaning drift and lip-sync, not just a render.

02.See It Work

Eight videos, one library gate.

This is the readiness checker, live. Click any video to see why it landed where it did, and change a field to watch the verdict move. It’s the same logic the workbook and the Python tool run.

Readiness checker — live

8 example videos · evaluated 2026-06-18

Library gate
HOLD
READY 1FIX 4BLOCK 3

VID-01 · real person, no consent

Avatar source

Consent artifact

Claim framing

Claim

Claim has basis

AI disclosure

Localization

BLOCKrule B1

Real person's face or voice in use with no completed consent artifact. A hard stop — complete the consent video / release for this person and use before publishing.

Change any field to see the verdict move. It reads the video's production structure, not a platform label. Resets on reload. Not legal advice.

03.The Runnable Checker

Run it offline. Get a verdict you can act on.

The Python checker reads a CSV of your videos and prints exactly this — per-video verdicts with the rule that fired, plus the library gate. No install, no network, deterministic. Here’s its output on the sample set:

================================================================
  AI Avatar Video Production Kit  (AVP-089)
  Evaluation date: 2026-06-18    Videos: 8
================================================================

  LIBRARY GATE:  HOLD
  READY 1   FIX 4   BLOCK 3

----------------------------------------------------------------
  [BLOCK ] VID-01-realperson-noconsent   (rule B1)
      source: custom_avatar_real_person / consent: none
      - Real person's face or voice in use with no completed
        consent artifact. Right-of-publicity and platform consent
        rules make this a hard stop. Complete the consent video /
        release for this person and use before publishing.

  [BLOCK ] VID-02-avatar-testimonial   (rule B2)
      framing: personal_experience
      - An avatar cannot deliver a first-person lived-experience
        testimonial - it has no experience, so the claim is
        unsubstantiable and a disclosure does not cure it.
        Reframe, or use real footage of the real person.

  [BLOCK ] VID-03-earnings-noproof   (rule B3)
      claim: health_or_earnings / basis: no
      - Unsupported health or earnings claim - deceptive on its
        face regardless of presenter or disclosure.

  [FIX   ] VID-04-stock-nolabel   (rule F1)
      - A talking-head avatar needs a clear-and-conspicuous
        disclosure that the presenter is AI-generated.

  [FIX   ] VID-05-bold-claim-thin   (rule F2)
      - Performance claim needs a reasonable basis. Substantiate,
        soften to what the evidence supports, or remove it.

  [FIX   ] VID-06-dub-not-qa   (rule F3)
      - A localized version was generated but not QA'd. Review
        for meaning drift, accuracy, and lip-sync before it ships.

  [FIX   ] VID-07-consented-endorse   (rule F4)
      - Consent and disclosure are in order; confirm a material-
        connection disclosure if the person is paid or affiliated.

  [READY ] VID-08-clean-explainer   (rule R1)
      - Consent not required, disclosure adequate, no
        unsupportable claim, dub QA'd. Publish.
----------------------------------------------------------------
04.The Standard

Three principles it holds to.

Consent before generation

If a real person's face or voice is involved, the consent artifact comes first. No artifact, no publish — the verdict is BLOCK until it's on file.

An avatar can't testify

It has no experience to recount. The kit blocks a personal-experience claim outright and points you to a framing that's actually true.

Disclose, then localize

Tell viewers the presenter is AI-generated, place it where they'll see it, and QA every dub before it ships. Structure over a platform toggle.

05.What This Is — And Isn't

Clear about the lane. No inflated promises.

What it is

  • A production pipeline plus a pre-publish readiness gate per video.
  • A consent-and-disclosure workflow you can hand to a team.
  • A documentation trail — consent artifacts and claim basis on file.

What it isn’t

  • Legal advice, or a substitute for counsel on high-stakes work.
  • An avatar generator — bring your tool (HeyGen, etc.); this gates the output.
  • A live legal database — platform and state rules need verifying at use.

Not legal advice. This is triage and documentation support. Platform consent requirements, state likeness law, and the EU AI Act Article 50 date move quickly; verify against primary sources and have counsel review anything high-stakes.

06.Who It's For

Built for the teams shipping avatar video at volume.

  • L&D and enablement teams scaling training video without re-filming
  • Marketing teams producing talking-head content at volume
  • Agencies offering avatar video as a service to clients
  • Founders localizing one message into many languages, compliantly
07.Pairs Well With

Build the rest of the synthetic-media stack.

Voice & Likeness Compliance Gate

Consent and disclosure across all synthetic media — the broader gate this kit's avatars sit inside.

AI Literacy & Workforce Training Kit

If your avatars present training, the turnkey literacy program they live inside.

Organic Social & Short-Form Video System

The creation layer — pillars, hooks, and scripts for the content your avatars deliver.

08.Common Questions

The questions teams actually ask before they publish an avatar video.

Whenever the avatar uses a real, identifiable person's face or voice. A stock or template avatar carries the platform's license and needs no separate artifact; a fully synthetic face needs none either. For a custom avatar of a real person, most tools require a recorded consent video before the avatar is created — treat that completed consent video, or a signed release covering the use, as the artifact. 'Pending' is not 'on file': a requested-but-incomplete consent does not clear the gate, and the verdict stays BLOCK until it's done.

Clear the video before it ships.
Not after.

One purchase, lifetime access, 12 months of updates. The checker, the workbook, the playbooks, and the sample set. $89, once.

Get the System — $89

Sold by RedHub AI LLC · Secured by Stripe · redhub.ai

Not legal advice. Triage and documentation support — platform consent rules, state likeness law, and the EU AI Act Article 50 date move quickly; verify at use and have counsel review anything high-stakes.