CAP v0.1 gives creatives verifiable proof of how AI was used - without getting in the way
AI is already in your stack: ideation, moodboards, drafts, assets, edits. The real problem isn't "if" you use it - it's proving "how" you used it when rights, consent, or attribution get questioned.
VeritasChain Standards Organization (VSO) has released CAP v0.1 (Content / Creative AI Profile), a new profile under the Verifiable AI Provenance (VAP) Framework. It creates a verifiable evidence layer for AI activity across creative workflows, so you can show your work with cryptographic receipts.
Why this matters to creatives and studios
Clients, partners, and platforms are asking tougher questions: Did you train on licensed material? Who ran that generation? Was pre-release content involved? Most teams can't prove it after the fact.
CAP closes that gap. It records what happened, when, by whom, and under what rights or consent - and makes tampering obvious.
What CAP is - and what it isn't
- It's not content moderation, an AI ban, or automated copyright policing.
- It doesn't judge quality, similarity, or legality.
- It's a transparent evidence layer you can point to when questions come up.
What gets recorded
- INGEST - when assets enter an AI system
- TRAIN - when models are trained or fine-tuned
- GEN - when content is generated
- EXPORT - when outputs are delivered or published
Each event includes rights basis, consent basis, confidentiality classification, user and role attribution, plus tamper-evident integrity guarantees. Think: receipts for every meaningful step.
Evidence-based accountability, not real-time policing
CAP focuses on preserving cryptographically protected records as work happens. That enables both proof of use and "negative proof" - for example, showing that a specific asset was not ingested or referenced during a project window.
That's useful for IP disputes, deepfake allegations, client audits, internal reviews, and regulatory inquiries. It keeps creative speed intact while giving your team a defensible paper trail.
Where CAP fits in your world
- Game development and publishing
- Film, animation, and streaming
- Publishing and editorial
- Music production and rights management
- Adult content platforms and consent-sensitive work
- Education, research, and professional training
- Brand, web, and investor communications
CAP v0.1 defines a minimal common set so you can adopt now, then extend for your niche as standards evolve.
How to put this to work fast
- Instrument your tools: Configure AI apps and internal systems to emit CAP events (INGEST, TRAIN, GEN, EXPORT).
- Set rights and consent defaults: Make rights/consent fields mandatory at ingestion and generation.
- Track roles: Log who did what under which authority (artist, producer, vendor, approver).
- Store verifiably: Use tamper-evident storage so records stand up to scrutiny.
- Audit routinely: Spot-check projects to confirm evidence matches creative intent and contracts.
Open draft - get involved
CAP v0.1 is a draft, non-normative specification released for discussion, testing, and feedback. It's published under a Creative Commons license and is openly available to studios, independent creators, researchers, auditors, and policy teams.
Read CAP v0.1 and implementation details
How this compares to related efforts
CAP focuses on logging AI lifecycle events and the rights/consent context behind them. It can complement media provenance signals and content credentials used at distribution time.
- C2PA - content provenance and authenticity signals embedded in media
- NIST AI RMF - guidance for managing AI risk across organizations
For creatives: protect your craft and your clients
- Pitch with confidence: Show verifiable proof of clean inputs and authorized use.
- Work with licensed sources: Tie licenses and consent to actual events, not a slide deck.
- Reduce revision drama: When someone asks "how was this made?" you can answer with facts.
Next step
If you're leading a studio or freelance team, assign a producer or tech lead to pilot CAP event logging on one active project. Start with ingestion and generation; add training and export as you go. The win is simple: faster approvals and fewer disputes.
Want structured upskilling for your team on practical AI use in creative work? Explore curated options here: AI courses by job.
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