We built a bot platform on Lambda but aren't persuing it, interested?

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Hello, We made a bot framework but have decided not to pursue it. Normally we would just shutter the project and move on to something else. The thing is that the product itself is really cool. I'd hate to just let it wither and die. I don't have anything specific in mind but if you're interested in this space (which just got hotter because of F8) then let me know and we can chat. Here is an example of a bot that manages a group text message chat room. https://medium.com/@jmathai/create-a-group-text-channel-in-under-a-minute-with-joule-using-twilio-and-aws-lambda-58a2d12450e8 It's not limited to bots. But it's a great use case of the platform. We have a few friends using it but haven't pushed it a wider audience. Details: * URL: https://joule.run * Documentation: https://joule.run/docs/quickstart * Tech: Python, Flask, EC2, Dynamo, Lambda, API Gateway, Vagrant, Node, NPM * Public source code: https://github.com/joulehq (mainly npm packages to help build Joules) * Code quality: Very good for an MVP

Visit product View on Hacker NewsApr 12, 2016

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

75%75% 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.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: using, code · Missing: mac, agents, macos

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

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

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

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

41%41% 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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