Instant Answers – Have 1:1 conversations with any given text source

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Hi everyone, We are Nico and Leo. We built an AI-powered chatbot builder designed to make it easy for anyone to create a ChatGPT-like chatbot in just minutes. If you're interested in trying it out, we offer a FREE plan that allows users to create and customize their own chatbot. It is ideal for people looking to add a support chatbot to their website or summarize complex information. Here are some of the key features: - Upload documents (PDFs, docs, txt, csv) or input a website URL, and we'll extract the information and build a chatbot that can answer questions related to the content. - Customize your chatbot's messages and appearance, and embed it as a chat widget (a bubble chat) or just embed it as an iframe on your website. - Use our chatbot builder to reduce your support tickets, save time on customer service, or help users get the information they need quickly. - Use the chatbot to summarize or get your questions answered about complex information (book, technical documentation, legal documents, etc) that is hard to read/understand or simply you don't want to read it completely. We'd love to hear your thoughts or feedback, so feel free to drop us a line in the comments or visit our website to learn more. Thanks for reading!

Visit product View on Hacker NewsMay 9, 2023

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

89%89% 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: user, chatgpt · Missing: mac, agents, macos

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: builder, users · Missing: plus, platform, intuitive

61%61% 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

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

10%10% 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.

Incorrect prediction on native model

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