TextAI – Native SMS AI assistant for individual and group chats

Hacker News

Hey HN community! Like many of you, I spend most of my day in text conversations. One day I found myself switching between group chats and various AI apps, and thought, why can't AI just live where we already chat? So I built TextAI. It's an AI that works right in your SMS app. No new app to download, no platform to learn. Just text +15626840069 to start chatting or add it to any group chat! The tech and stack details: - Native SMS/MMS integration with context management across conversations - Handles multiple participants, learns group preferences, and scales for concurrent chats - Able to converse in multiple languages - Built with Twilio on top of a foundational LLM model, plus building my own domain logic on top Some cool things people have used it for: - A group of my friends used it to plan a weekend trip to Las Vegas last week. It was their first time there. They used it to get suggestions on the must-do activities, casinos to play at, and finding restaurants that worked for vegetarians and meat lovers. - A high school student showed the power of AI and started a group chat with their grandpa! - my personal fav - A couple who used it to find new hiking trails around where they live without arguing for their preferences I built this because I believe AI should be accessible through existing communication channels, not locked in new apps. It should be accessible to all, and frankly, it's important to keep things simple. Hope you find it useful, and I would love your feedback, the good and the bad! Thank you for reading!

Visit product View on Hacker NewsJan 23, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apps, new · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, apps · Missing: mobile apps, ios, entrepreneurs

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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

17%17% 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.

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