About Adgentek
Adgentek is an ad server for AI apps that delivers labeled native ads inside conversational interfaces. It classifies conversations in real time to produce derived signals—intent category, decision stage, and topic—without forwarding raw transcripts or personal data to advertisers.
Ad requests run in parallel with model completions to avoid added latency, and ad units render client-side in a publisher-controlled slot with a visible "Sponsored" label. A demand waterfall (direct, programmatic, CPC, and outcome-priced buyers) increases fill by routing requests through successive tiers.
Integration is available via a compact JavaScript Web SDK or an install prompt for coding agents, with placement, format, and category controls managed in the publisher dashboard. Publisher controls include placement timing, format selection, category and brand blocklists, frequency caps, and minimum quality floors.
Reporting provides fill, eCPM, and revenue by slot, and safety filters exclude sensitive topics to prevent inappropriate ad placements.
Key Features
Use Cases
Who is it for?
Ad requests run in parallel with model completions to avoid added latency, and ad units render client-side in a publisher-controlled slot with a visible "Sponsored" label. A demand waterfall (direct, programmatic, CPC, and outcome-priced buyers) increases fill by routing requests through successive tiers.
Integration is available via a compact JavaScript Web SDK or an install prompt for coding agents, with placement, format, and category controls managed in the publisher dashboard. Publisher controls include placement timing, format selection, category and brand blocklists, frequency caps, and minimum quality floors.
Reporting provides fill, eCPM, and revenue by slot, and safety filters exclude sensitive topics to prevent inappropriate ad placements.
Key Features
- Real-time conversation classification into intent category, decision stage, and topic without forwarding raw transcripts or personal data
- Ad requests run in parallel with model completions to avoid added latency
- Client-side rendering of labeled native ad units in publisher-controlled slots with visible "Sponsored" label
- Demand waterfall routing through direct, programmatic, CPC, and outcome-priced buyers
- Integration via compact JavaScript Web SDK or install prompt for coding agents with publisher dashboard controls for placement, format, and category
Use Cases
- Monetize AI chatbots and virtual assistants with Adgentek by serving privacy-preserving in-chat native ads that rely on client-side real-time intent classification (no raw transcripts exposed), run parallel low-latency ad requests, and use dashboard controls plus demand‑waterfall routing to optimize revenue
- Integrate Adgentek into voice and messaging apps to surface contextual offers and promotions during conversations using safety filters and labeled intent tags for accurate targeting while rendering ads client-side for user privacy, with reporting to measure engagement and conversion
- Enhance e-commerce and customer-support conversational flows by recommending products and time-sensitive deals via in-chat native ads, leveraging real-time intent classification, demand-waterfall monetization to prioritize high-value demand, and admin controls for campaign management and compliance
Who is it for?
- Ai app developers
- Chatbot and conversational interface publishers
- Product managers and monetization teams
- Ad operations teams
- Frontend and platform engineers integrating sdks
- Programmatic advertisers and ad buyers
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