ThreadWise – Your AI assistant via email

Hacker News

Hi HN, I built ThreadWise to make accessing AI as easy as sending email. You can email prompts directly to your ThreadWise address and get instant AI-powered responses, essentially an always available co-worker. Another great feature is the ability to schedule recurring tasks and since the AI has web access, you can get things like: Daily mortgage rates or airfare price monitoring Weather and news summaries Sport scores, jokes, quote of the day Pull data from public APIs (and more) So you can essentially use it as a personal newsletter, crafted to your taste. The free tier will let you test this out for free! I am looking for some feedback/criticism, testing, and additional ideas and I am open for collaboration if you have experience with sales. Also open to hearing which scheduled tasks people would find most useful. Why I built it: I noticed a trend online, as well as with family/friends, that people would like to have a quick access to AI in instances where they couldn't always install apps or use browser-based tools (such as in remote/low bandwidth environments). This is when it him me, email clients already have all the features needed to interact with an AI (text + attachments) and I quickly got to work. Some of the advantages are also that since there are no new apps, or browser tabs needed, the tool is ideal for companies who don't have the bandwidth to setup full fledged AI solutions on their own. The companies can choose either between public LLMs (e.g. OpenAI) or host everything on-premise with locally run models, so no data ever leaves the premises. Eager to hear what you all think!

Visit product View on Hacker NewsApr 27, 2025

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

90%90% 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.

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.

AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

48%48% 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

30%30% 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: recurring · 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 · Missing: web3, chat, crypto

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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