Eva – An AI Store Assistant for Restaurants

Hacker News

Hello HN! Introducing "Eva", our AI store assistant designed to transform customer engagement in restaurants. Eva provides real-time interactions, from answering questions to handling orders. Currently, Eva is integrated with TPass, a platform tailored for bubble tea shops. We're enthusiastic about the initial results and are considering expanding its horizons. Link to try out or download: https://foreva.ai We're at an exciting phase of Eva's journey and would love insights on: - Possible technological improvements. - Unique use cases you might envision. - Thoughts on market expansion and broader integration. Any feedback, big or small, would be invaluable. Thank you for your time and insights!

Visit product View on Hacker NewsAug 24, 2023

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71%71% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

24%24% 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

9%9% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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