Create custom AI chatbots with your data, no coding required

Hacker News

StartConvo is a new AI platform that enables anyone to create and deploy custom AI chatbots trained on their own data, with easy website integration. Key features: Data upload for custom AI training One-click website integration No-code interface Scalable from personal projects to enterprise Privacy-focused (your data stays yours) Use cases: 24/7 customer support Improved user engagement Personalized user experiences Knowledge base assistants We're offering 25 free credits for early adopters. Looking for feedback from the HN community on the concept, implementation, and potential use cases.

Visit product View on Hacker NewsJul 31, 2024

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

81%81% 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, new, coding · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, 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

39%39% 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: personal · Missing: mobile apps, ios, entrepreneurs

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

12%12% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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