LinkAffix turns the product recommendations your AI already makes into affiliate revenue with one server-side API call, no cookies and no client-side code. Most affiliate tracking depends on browser JavaScript and third-party cookies that don't exist when your ‘page’ is a streaming LLM response. LinkAffix solves this with first-party, server-side attribution: send us your LLM's response text, get back the same text with tracked affiliate links woven into the real product mentions already in it.
I'm Ayush, builder of LinkAffix.
I built this because affiliate tracking is stuck in the past: third-party cookies and browser JS, neither of which exist when your "page" is an LLM streaming text server-side. AI products that recommend real products (shopping assistants, trip planners, gift finders) currently have zero way to earn commission on those recommendations.
LinkAffix is one API call: send your LLM's response text, get back the same text with tracked affiliate links woven in. No cookies, no client JS, first-party attribution.
It's live and free to try today (1,000 injections/month, no card). Today affiliate links are configured manually per campaign. Native Amazon/CJ/Rakuten import is next on the roadmap.
Would love feedback on: whether the attribution model make sense for how you're building, what affiliate networks should I prioritize integrating first, etc. Happy to answer anything.
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A bulk endpoint or batch mode would be huge for high-volume apps. Right now I imagine each response text means a separate API call, which adds latency and costs when you're processing thousands of completions an hour. Letting us send an array of LLM responses in one request would make server-side integration way more practical for production workloads.
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Would love to see a confidence score returned with each rewritten link so I can flag or override any recommendation my model made that the API decided not to monetize, keeps editorial control in our hands.
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A bulk endpoint or batch mode would be huge for high-volume apps. Right now I imagine each response text means a separate API call, which adds latency and costs when you're processing thousands of completions an hour. Letting us send an array of LLM responses in one request would make server-side integration way more practical for production workloads.
Would love to see a confidence score returned with each rewritten link so I can flag or override any recommendation my model made that the API decided not to monetize, keeps editorial control in our hands.