AI disclosure for agencies
One AI disclosure workflow across clients, markets and platforms
Agencies can use Disclara's free checker now to decide what to disclose, identify the platform action and download evidence for each assessed asset. The proposed Agency workspace would add saved client history, team approvals and campaign bundles; none are part of the current public product.
Available now without an account: checker and evidence download. You retain the downloaded file.
Product availability
What agencies can use now
Use the public checker and download each result today. Shared workspaces, retained records and subscriptions are planned and not available yet.
Available now
Free checker and browser-only tools
Run a disclosure check and download its evidence without an account. Disclara does not retain the downloaded record; keep your own copy.
Check disclosure — free →Planned
Team and Agency workspaces
Paid workspaces are not available yet. Saved history, team review and client spaces are proposed features. Early-access signup is not open yet; no subscription or trial starts from this site.
See planned pricing →Designed around agency delivery
AI disclosure for every agency workflow
AI disclosure for marketing agencies
Keep campaign claims, EU requirements, destination-platform rules and each client’s internal AI policy in one decision context before media goes live.
Outcome: Consistent disclosure decisions across paid, owned and client-delivered assets.
AI disclosure for creative agencies
Record which components were generated or edited — from product backgrounds and generative fill to virtual models, synthetic spokespeople and AI voice-over.
Outcome: Component-specific wording that does not mislabel the entire creative.
AI disclosure for social media agencies
Separate the legal assessment from the native label and publishing workflow used by TikTok, Instagram, YouTube, LinkedIn and other channels.
Outcome: A platform action and evidence record for every scheduled asset.
One operating model
Multi-client AI policy management
The same asset can require different handling because a client sets a stricter internal policy, targets another market or publishes through a platform with a different native label. The planned Agency workspace keeps those layers separate instead of hiding them inside one generic compliance status.
One shared baseline, separate client overlays
- Reuse the same source-backed EU and platform rules.
- Attach the client’s own disclosure threshold and required wording.
- Keep client decisions and evidence separated.
- Review rule changes against affected campaigns.
Production governance before disclosure
Approve the AI production stack, not only the finished asset
The same tool can be approved for product-background work and prohibited for a synthetic testimonial. The browser-only Production Stack Preflight and optional checker API schema can evaluate a supplied tool-policy snapshot now; a retained registry, organization policies and automated procurement workflow remain planned workspace capabilities.
Organization tool profile
Record the vendor, policy version, allowed media and markets, restricted uses, provenance capability and last verified evidence.
Client and campaign overlay
Resolve client approval, intended use and required human review for the exact campaign rather than certifying a vendor globally.
Independent disclosure decision
Keep permission to use the tool separate from legal disclosure, platform policy, rights and the state of the final rendition.
Available now without an account: a browser-only campaign preflight, downloadable JSON and the public checker API when the caller supplies these fields. There is no retained registry, durable policy store or automated vendor verification yet. Run AI Production Stack Preflight → Open the versioned input contract →
Decision provenance, not another DAM
Connect the content supply chain without duplicating the media library
Bynder, Fotoware, Adobe or another DAM should remain the asset system of record. Disclara links the external asset and version IDs, rendition hash and observed provenance snapshot to the AI Usage Manifest, rule version, disclosure decision, human approval and publication evidence.
See the DAM decision-provenance model →Integration boundary
- DAM: binaries, derivatives, lifecycle and distribution metadata.
- Disclara: permission, disclosure rationale, rule snapshot and approval evidence.
- Export gate: verify that provenance still exists on the final rendition.
- Fail closed: incomplete, unknown or lost provenance routes to review.
The schema accepts user-supplied or connector-reported references. Live DAM connectors and automatic file retrieval are planned and are not currently available.
Policy overlays
Client-specific disclosure policies
Disclara’s model treats a client rule as its own decision layer. It can be stricter than law or platform policy without being misrepresented as a legal requirement.
| Client context | Example internal policy | Workflow effect |
|---|---|---|
| Consumer brand | Disclose every visible AI-generated scene component. | Require component-specific wording before approval. |
| Talent campaign | Human review and consent evidence for synthetic voice or likeness. | Hold publication until the accountable reviewer resolves the evidence. |
| B2B campaign | Follow the EU baseline and each platform’s native-label workflow. | Show legal and platform findings as separate actions. |
Examples illustrate the policy model; they are not universal rules or customer configurations.
Evidence per deliverable
Campaign evidence records
A disclosure decision should remain attached to the asset after the campaign leaves the creative team. The current checker can download a canonical JSON evidence envelope that distinguishes the approved version from the served variant. The planned Agency workspace adds client-level organization and campaign export.
See the Evidence Report model →Each asset record includes
- Approved AI tool profile, policy version and client-specific permission
- Allowed content types, markets, restricted use cases and required approval
- External DAM asset/version ID, exact rendition hash and provenance observation
- Approved asset version ID and SHA-256 hash
- Permitted platform transformations and human re-approval requirement
- Served asset hash, generated-variant flag and creative diff status
- Disclosure and provenance state of the served variant
- Declared AI tools and affected components
- EU and destination-platform findings
- Client-policy overlay and required action
- Planned publication and campaign dates
- Rule effective window and scheduled recheck
- Person, channel, territory and validity-scoped rights attestation
- Authorized-asset comparison and preserved incident snapshot
- Observed enforcement recorded separately from law and policy
- Exact disclosure wording used
- Reviewer, decision time and rule versions
Accountable approval
Reviewer workflow
Deterministic rules handle repeatable decisions. Human reviewers own uncertainty, consent, likeness and exceptions — with their decision recorded before publication.
Approve an asset version
Record the exact client-approved version, hash, media, AI usage, destination, market and people represented.
Set permitted transformations
Record whether platform AI modification is permitted and whether any transformed variant needs new human approval.
Upload to the platform
Keep the campaign, uploaded asset and configured disclosure or provenance controls connected to the approved record.
Capture the served variant
Preserve what an audience actually received, including its hash, visible disclaimer and available provenance state.
Compare approved vs served
Classify the creative diff and route material, inconclusive or out-of-permission transformations to a human reviewer.
Verify and close evidence
Confirm legal, platform, disclosure and provenance outcomes independently; observed enforcement cannot waive them.
The current checker supports the rule check and evidence download. Shared queues, roles and four-eyes approval are planned workspace capabilities.
Illustrative operating scenario
Agency publishes 140 assets for 8 clients across TikTok, Instagram and YouTube
Before
Disclosure decisions live in scattered handoffs
- Client policies sit in separate briefs, documents and message threads.
- Teams repeat legal and platform lookups for similar assets.
- Disclosure wording varies between creators and channels.
- Reviewer decisions are difficult to reconnect to the final file.
- A platform-generated variant can differ from the client-approved creative without a preserved comparison.
- Campaign evidence has to be reconstructed when a client asks.
Target workspace workflow · planned
Every asset follows the same evidence path
- AI use, market, platform and client policy become structured inputs.
- Versioned rules produce separate legal and platform findings.
- The approved asset, transformation permission and served variant are compared before the record is closed.
- Observed enforcement never overrides law, policy, permissions or provenance.
- Recommended wording names the generated component accurately.
- Uncertain cases route to an accountable reviewer.
- Each final decision produces an evidence record for client reporting.
This is an illustrative workflow, not a customer case study or measured productivity claim. Multi-client workspace automation is planned; the core check and evidence download can be tested now.
Start with the current product
Check a real asset and keep the decision yourself
Use the checker and its download today. The planned Agency workspace is not available for subscription, trial or early-access signup.
Disclara separates binding law, platform policy, client policy and recommended wording. The checker is source-backed information, not legal advice. Review the sources and methodology.