Monetize your LLM Apps in 5 minutes

Hacker News

Firebender is a streamlined advertisement integration for LLM app developers. We aim to: - Enhance the user experience through the integration of real-time, contextually relevant advertisements. - Offer a sustainable source of income for LLM app developers. In just 2 steps you can start making ad revenue: 1. Join our early beta through our waitlist at https://www.firebender.ai/ 2. Add a GPT “action” to your LLM app that calls our service when it wants to serve a contextual ad during the conversation. We’re early in development and looking for potential customers to work with! If you’re interested, join the waitlist and check out our demo at https://www.firebender.ai/

Visit product View on Hacker NewsNov 14, 2023

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5points

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, context · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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