Thrad Safety Center

Thrad Safety Center

Thrad Safety Center

Building a responsible future for advertising in AI conversations

Building a responsible future for advertising in AI conversations

Building a responsible future for advertising in AI conversations

Building a responsible future for advertising in AI conversations

Building a responsible future for advertising in AI conversations

LLMs introduce an entirely new way for people to discover products, make decisions, and receive guidance. Advertising in these environments must therefore meet a higher bar for transparency, consent, and user protection. This Safety Center outlines how Thrad approaches safety for everyone in the ecosystem consumers, advertisers, and publishers the standards we believe the entire industry should uphold.

LLMs introduce an entirely new way for people to discover products, make decisions, and receive guidance. Advertising in these environments must therefore meet a higher bar for transparency, consent, and user protection. This Safety Center outlines how Thrad approaches safety for everyone in the ecosystem consumers, advertisers, and publishers the standards we believe the entire industry should uphold.

Consumers

Consumers

Transparency, control & protection

Transparency, control & protection

Publishers

Publishers

unbias reliable monetization

unbias reliable monetization

Advertisers

Advertisers

Responsible safe advertising

Responsible safe advertising

Why LLM ad safety matters

LLM ads are clearly labeled as ads. But labeling alone is not enough. In conversational interfaces, the boundary between content and persuasion becomes thinner. Users often perceive AI responses as guidance from a trusted assistant, not a traditional advertisement. That means even ethically placed ads must be designed with care, limits, and user first principles.

We believe LLM advertising should enhance decision making not manipulate it.

LLM ads are clearly labeled as ads. But labeling alone is not enough. In conversational interfaces, the boundary between content and persuasion becomes thinner. Users often perceive AI responses as guidance from a trusted assistant, not a traditional advertisement. That means even ethically placed ads must be designed with care, limits, and user first principles.

We believe LLM advertising should enhance decision making not manipulate it.

Opt out right

Every LLM app or platform using Thrad must provide users with ad-visibility controls and abide by clear disclosure requirements.

Responsible monetization without compromising trust

We conduct regular reviews of publisher inventory to prevent unsafe manipulation, mislabeling, or steering.

Transparent

Transparent

Every LLM app or platform using Thrad must provide users with ad-visibility controls and abide by clear disclosure requirements.

Visible

Visible

Every ad delivered through Thrad is explicitly labeled as sponsored content. No hidden influence, no ambiguity.

Ethical

Ethical

Ads appear only when relevant to the users stated intent. We reject ads that aim to shift the conversation unnaturally or exploit sensitive topics.

Explainable

Explainable

Users can learn why an ad appeared, what context triggered it, and which advertiser paid for it.

Controlable

Controlable

Every ad must respect conversational settings. Ads cannot overwhelm, pressure, or steer users toward harmful decisions.

Reviewed

Reviewed

Creatives go through automated and human in the loop review to ensure accuracy, safety, and compliance with global standards.

Thrad is AI-native

Advertising designed for LLMs, not retrofitted from web

Advertising designed for LLMs, not retrofitted from web

Traditional ad tech was built for pages and clicks. Thrad is built for prompts, conversations, and agentsmatching ads to real intent, not cookies or third-party IDs.

Our Safety Guarantees

Our Safety Guarantees

Our Safety Guarantees

Thrad is built on five commitments:


Thrad is built on five commitments:


Transparency

Clear labeling, clear logic, clear explanations.

User First

Ads must help users, not confuse, pressure, or manipulate them.

Contextually Relevant

Ads appear only when directly relevant.

Independent Governance

We engage with researchers, ethicists, regulators, publishers, and advertisers to refine our policies.


Continuous Monitoring

We evaluate emerging risks in AI behavior, model updates, and prompt techniques to strengthen our safeguards.



Continuous Monitoring

We evaluate emerging risks in AI behavior, model updates, and prompt techniques to strengthen our safeguards.




Industry Standards We Advocate For




Industry Standards We Advocate For




Industry Standards We Advocate For


Universal Ad Disclosure Format (UADF)

Universal Ad Disclosure Format (UADF)

A consistent, platform-independent way to label conversational ads.

Brand Safety Taxonomy

Brand Safety Taxonomy

A shared framework to determine when an ad can appear and when it must be blocked.

Contextual-only ad targeting

Contextual-only ad targeting

No cross-platform tracking, identity stitching, or behavioural profiling.

Reporting of influence risks

Reporting of influence risks

Platforms should disclose how ads interact with their model behavior, reasoning patterns, and assistant persona.


Reporting & Feedback

If you believe an ad was unsafe, misleading, or improperly placed,

you can report it directly from any Thrad enabled surface.

Our team reviews every escalation.

For questions or concerns, contact: safety@thrad.ai



Reporting & Feedback

If you believe an ad was unsafe, misleading, or improperly placed,

you can report it directly from any Thrad enabled surface.

Our team reviews every escalation.

For questions or concerns, contact: safety@thrad.ai