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 user’s 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 agents—matching 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
Menu
Contact Us
+14152987869
600 California St San Francisco, CA 94108
contact@thrads.ai
© 2025 Thrad. All rights reserved.
Menu
Contact Us
+14152987869
600 California St San Francisco, CA 94108
contact@thrad.ai
© 2025 Thrad. All rights reserved.
Menu
Contact Us
+14152987869
600 California St San Francisco, CA 94108
contact@thrads.ai
© 2025 Thrad. All rights reserved.
