AI is now the primary interface for
research, comparison, and decision-making
Developers are building AI apps faster than ever, but monetization lags
Subscriptions alone don’t scale due to rising inference costs
Legacy ad models disrupt experience and erode trust

Koah enables native monetization for AI apps


• Lightweight SDK installs in minutes
• Native formats that match your product
• Start monetizing immediately

• Premium placements in AI apps
• Target user intent in real time
• 2% average CTR from AI conversations
at scale
Frequently asked questions
How long does it take to implement Koah?
Most partners go live in minutes to a few hours. Koah provides a lightweight SDK for web, iOS, Android, and Flutter. After creating an account and adding your Publisher ID, you can place native ad units directly inside your AI chat or search interface. Our team supports initial setup to ensure placements are optimized for performance and user experience. For most AI apps, implementation requires minimal engineering resources and no complex infrastructure changes.
Can we control which advertisers appear?
Yes. Publishers have control over advertiser categories and can apply brand safety preferences. Koah works with premium brands and ensures ads are aligned with your app’s audience and community standards. Because ads are served contextually within AI conversations, they are matched to relevant topics in real time — but you retain oversight over the types of advertisers that can appear in your experience.
When are payouts made?
Koah pays publishers on a net 30 basis after the close of each month. You can track impressions, clicks, CTR, and revenue inside your dashboard in real time. Payments are issued once minimum payout thresholds are met, and our team provides transparent reporting so you always know how performance is trending.
How does Koah decide which ads are displayed?
We give you the option to choose from different ad formats based on your integration needs and user experience goals. Each format has specific placement options and interaction models.









