Let Agent handle your bookings, cancellations, and negotiations

Hacker News

Introducing PineAI, your personal assistant designed to tackle life's problems for you. For instance, you can have it call your telecom's customer service hotline to negotiate a lower bill, or ask it to cancel unwanted subscriptions. Need local restaurant recommendations, descriptions of their specialties, and a table booked? PineAI can handle that too. Essentially, you can delegate any task you'd rather not do yourself. PineAI is remarkably intelligent – it proactively gathers information, initiates contact autonomously, and works diligently to achieve your goals. By taking care of those burdensome tasks, PineAI frees up your time so you can enjoy life more. PineAI is also a valuable ally for individuals who find phone calls challenging. This includes international students navigating language barriers, deaf or hard-of-hearing individuals who rely on phone communication, and those experiencing social anxiety. PineAI is your trustworthy personal assistant. Start delegating your tasks today and experience the convenience!

Visit product View on Hacker NewsMar 29, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, tasks · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

32%32% 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 · Strong signals: arr, subscription, active · Missing: mrr, revenue, profit

17%17% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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