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Airstrip – An open-source platform to build and use internal AI apps

Hacker News

Airstrip – An open-source platform to build and use internal AI apps

Hey everyone, my cofounder and I are building Airstrip - https://github.com/hendychua/airstrip . Airstrip helps you manage your company's use of AI by providing a platform to integrate with your desired AI services and build internal AI apps for your employees. Here's a quick demo video: https://youtu.be/WREhMJMZmJA As AI usage becomes more common, companies want to carefully regulate which AI services they use and control what data is being sent to ensure data security and compliance. Building and using internal apps that use AI to streamline operations is also a common use case. This is where Airstrip can help. The platform allows you to add integrations with different AI services with your own API keys. You can restrict which teams can use these API keys. Admins can build internal AI apps by prompting. Members can use these internal apps. This way, companies are assured that their employees are not going to a bunch of different AI services (ChatGPT, Anthropic, etc) on their own. Airstrip is currently focused on making it easy for non-technical users to build AI apps - anyone (your HR team, operations team, etc) can build AI apps by prompting because they are the ones with domain knowledge (and it frees up engineers to build other more complex apps). We are not a workflow tool nor prompt management tool (at least not yet). These are features that we have in our plan but we are focused on making it as easy as possible for non-technical users to build apps. Airstrip is completely open-source and easy for you to get started. It is in its early stages and we are adding more features. Appreciate if you try it out and give us your feedback. Thank you!

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, chatgpt · Missing: mac, agents, macos
95%95% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, video, users · Missing: mobile apps, ios, personal
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
34%34% 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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