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I made a cheaper alternative to customer support AI agents

Hacker News

I made a cheaper alternative to customer support AI agents

Hello, I'm Ezz. I left my full-time data engineering job 3 years ago and then got into freelancing. Saw an opportunity on Upwork until I gained the Top-Rated Plus badge. Then I got almost zero customers for several months. I knew that it was my fault since I used Upwork as my only channel to support my family. I didn't lose hope and I applied more proposals until I saw a Saudi client who's interested in building a WhatsApp-based AI chatbot for his hotel. He accepted my proposal and interviewed me and got the offer. I was so happy and I told myself I'd never be at the same '5-month no money' situation as before. So I started building Sadiq Agent alongside my gig. It's an AI agent customer support for websites. I'm not saying it's the best AI agent support tool out there because this is just the beginning. But if you just need a chatbot embedded into your website that can retrieve knowledge base from your documents (or your website URLs), Sadiq Agent is THE tool that you need. If you want just a tool that can reduce the stress of your customer service reps asking very boring repetitive questions, Sadiq Agent is THE tool you need. If you want just a tool that can turn your conversations with customers into booked meetings 24/7, Sadiq Agent is THE tool. That's why it's a lot cheaper than the alternatives. You get start for free and I'm all ears. Your feedback is much appreciated. P.S. sorry guys, the free plan is not very generous b/c I'm very tight in budget

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, new · Missing: mac, macos, cursor
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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