UsefulAI – a tool to easily integrate AI/ML features into products

Hacker News

My co-founder and I worked with over 30+ companies in the last 5 years building and integrating AI/ML in their business and products. We’ve experienced how difficult it was to find, train, and deploy Machine Learning models to production even with an experienced team of data scientists and ML engineers. We would like to empower even the smallest teams to integrate (useful, not just hype) AI/ML features in their products: From speech recognition, image analysis to GenAI and from big cloud providers to niche players. In short we help you 1/find the AI/ML features that best meet their needs, 2/test them directly in the platform and 3/integrate them using one unique API. Feel free to try it! I’d love to get your feedback or just chat to learn more about how we can make AI integrations simpler.

Visit product View on Hacker NewsSep 5, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

84%84% 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: mac, model, models · Missing: agents, macos, agent

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, 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

42%42% 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: platform · Missing: plus, intuitive, reviews

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% 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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