Airbolt AI - The only way to add AI to your app with zero backend code
by•
Airbolt lets you securely call LLM APIs with zero backend. Just add our client SDK to your app and start making inference calls with best practices built in.
@andy_day1 What stood out about Airbolt to you? Always interested in first impressions.
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💎 Pixel perfection
Love the idea of skipping that overhead and still keeping things safe. Curious—do you already support mobile SDKs or is that still on the roadmap?
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Maker
@viktorgems thanks! Right now we only have a web SDK but adding mobile is at the top of our backlog and will be released soon!
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@mark_watson_28 Looking forward to that. Good luck to you guys!
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Congratulations on the launch guys, the product looks awesome. I really like the security focus, I think after seeing the downfall of Tea it's something the industry really needs!
What was the biggest learning curve for you in terms of the development?
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Maker
Thanks @theo_crewe_read ! Honestly, we've been trying to move fast and initially maintaining both a fully open source and managed version was slowing us down. We've decided to focus on the managed/cloud for now (because that's what makes it truly as easy and fast as possible) and rethink our open source strategy. While we're still committed to open source and building in public, it might look different, like SDKs and libraries.
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Congratulations Airbolt team! Excited to try a product that makes AI integration safe and easy!
So just thinking about this here... you could enable some really powerful capabilities with almost no additional prompt engineering effort. You already mentioned the control plane and guard rails which i assume could be proxy side but having hooks on backend as well as frontend really opens up a lot of options to dynamically alter llm inputs, outputs, and user interface.
I am thinking of my app switching to short form responses when screen space is tight. Maybe providing auto suggested responses in a button or dropdown on mobile devices but having that feature (and its associated llm overhead) toggled on desktop.
Genuinely excited by what you are starting here.
Prepare yourself for feature requests....from me :)
@derek_barnhart Awesome feedback. Mark and I were just talking about something similar the other day. While it would be super convenient for vibe coders to be able to configure everything from the dashboard, being able to dynamically set and adjust from the front end also unlocks so many use cases.
Great work @mark_watson_28 and team! 👏 As a PM, I can see Airbolt saving tons of time for companies wanting to add smart features—like AI chatbots, AI-generated content suggestions, or smart analytics—without worrying about backend hassles.
The no-backend, plug-and-play setup feels easy and perfect for building prototypes, powering smart workflow automation, dynamic user experiences, or integrating AI-driven decision systems at scale. I'm Excited to see what upcoming features are next on your roadmap? Are you planning to add analytics, new model integrations, or advanced team collaboration in the pipeline? Can't wait to see your growth!🔥
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Maker
@sneh_shah thanks! Some of the most immediate features are:
Supporting many more providers beyond OpenAI (and automatic failover and dynamic dispatch)
Bring-your-own-auth (lock down the inference API with your existing Auth0, Clerk, Firebase, etc auth)
Super simple RAG/Vector search
Mobile SDKs
That said, we're working with early users to really drive prioritization based off of real use cases!
And, we want to continue to add functionality to our self-service dash so that you can "upgrade" your AI without having to modify your source or redeploying.
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Maker
@mark_watson_28@sneh_shah Thanks for the feedback! Would love to hear how you'd prioritize the additional features you mentioned
Super slick way to cut backend hassle. How are you thinking about enterprise readiness (e.g. SOC 2) as teams scale on Airbolt?
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Maker
@monzures it's something that we've considered but isn't a current top priority just based on our current users and their use cases. That said, we're constantly learning and reprioritizing. There's nothing preventing us.
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So Airbolt honestly feels like it was built for anyone who’s ever tried to do some quick AI project and immediately hit a wall. You know that moment where you wanna plug in OpenAI and get some vibes going, but suddenly you’re in backend hell—something you did not sign up for, and it totally kills your flow. But with Airbolt, you just sign up, add their SDK, and fire off API calls right from your app frontend, like, “okay, let’s actually ship something tonight” kind of fast.
The security stuff is actually legit and doesn’t feel heavy-handed. They do short-lived JWTs and keep your provider keys locked down, plus IP throttling and origin allowlists so no one messes up your repo or blows your API budget. You don’t see secrets leaking everywhere, which is usually why I’m sketched out by frontend AI work—this is literally safe by default and it doesn’t get in your way. Plus it’s got that thing where you can switch between AI models and provider configs—like, live, with a dashboard, no redeploy, no more “hey we have to push a new build just to change a prompt.” That’s super clutch if you’re experimenting, doing some quick hackathon demo, or rolling out updates for a bunch of random plugins and extensions.
Honestly, it’s wild how you don’t need a backend for rate limits or abuse controls. Airbolt just absorbs that pain—per-user tokens, spend caps, so trolls can’t spike your bill while you’re vibing. And I’m hype about the vendor-neutral part. Switch OpenAI out for Anthropic or whatever comes next, all config-based, plus failover on deck. So you’re not locked into one model and you don’t have to argue with your cofounder about migrating APIs every two months.
Airbolt’s ideal for anyone doing AI stuff but not full-stack heavy: micro-SaaS peeps, product managers, Chrome and Discord bot builds, quick MVPs, or those experimenting with random ideas at 2 AM and want it live, not just sitting in a folder. Extension devs especially get how much it sucks to manage keys and infra—Airbolt gets rid of that stress. And it’s kinda fun to just drop in a React chat and see something work without spending all night on boilerplate, permissions, and worrying about whether the API key is public somewhere.
The open-source part is cool—like, the repo is active, the team actually responds, and the contributor energy matches that indie dev life. Feels like it’s being built in real-time with people using it for actual projects, not just for “enterprise pipeline” stuff. There’s not this big formal barrier; you can just jump in and the tool feels flexible enough to meet what you’re doing, however random. So yeah—it’s clean, it’s safe, doesn’t lock you down, does what you want right when you ask for it, and is clearly made for builders who vibe and iterate instead of planning in long sprints. You can test, swap models, pivot use cases, and keep secrets secret, all while shipping stuff fast. Not much more you can ask for when you just wanna ship and let the LLMs do the heavy lifting
Replies
Very cool! Best of luck with the launch
@andy_day1 🙏
@andy_day1 What stood out about Airbolt to you? Always interested in first impressions.
Love the idea of skipping that overhead and still keeping things safe. Curious—do you already support mobile SDKs or is that still on the roadmap?
@viktorgems thanks! Right now we only have a web SDK but adding mobile is at the top of our backlog and will be released soon!
@mark_watson_28 Looking forward to that. Good luck to you guys!
Congratulations on the launch guys, the product looks awesome. I really like the security focus, I think after seeing the downfall of Tea it's something the industry really needs!
What was the biggest learning curve for you in terms of the development?
Thanks @theo_crewe_read ! Honestly, we've been trying to move fast and initially maintaining both a fully open source and managed version was slowing us down. We've decided to focus on the managed/cloud for now (because that's what makes it truly as easy and fast as possible) and rethink our open source strategy. While we're still committed to open source and building in public, it might look different, like SDKs and libraries.
Congratulations Airbolt team! Excited to try a product that makes AI integration safe and easy!
@kat_watson Thank you twin!
Congrats on the launch!
So just thinking about this here... you could enable some really powerful capabilities with almost no additional prompt engineering effort. You already mentioned the control plane and guard rails which i assume could be proxy side but having hooks on backend as well as frontend really opens up a lot of options to dynamically alter llm inputs, outputs, and user interface.
I am thinking of my app switching to short form responses when screen space is tight. Maybe providing auto suggested responses in a button or dropdown on mobile devices but having that feature (and its associated llm overhead) toggled on desktop.
Genuinely excited by what you are starting here.
Prepare yourself for feature requests....from me :)
@derek_barnhart yes, keep them coming!
@derek_barnhart Awesome feedback. Mark and I were just talking about something similar the other day. While it would be super convenient for vibe coders to be able to configure everything from the dashboard, being able to dynamically set and adjust from the front end also unlocks so many use cases.
Congrats and good luck!
@michael_totah Thanks!
Great work @mark_watson_28 and team! 👏 As a PM, I can see Airbolt saving tons of time for companies wanting to add smart features—like AI chatbots, AI-generated content suggestions, or smart analytics—without worrying about backend hassles.
The no-backend, plug-and-play setup feels easy and perfect for building prototypes, powering smart workflow automation, dynamic user experiences, or integrating AI-driven decision systems at scale. I'm Excited to see what upcoming features are next on your roadmap? Are you planning to add analytics, new model integrations, or advanced team collaboration in the pipeline? Can't wait to see your growth!🔥
@sneh_shah thanks! Some of the most immediate features are:
Supporting many more providers beyond OpenAI (and automatic failover and dynamic dispatch)
Bring-your-own-auth (lock down the inference API with your existing Auth0, Clerk, Firebase, etc auth)
Super simple RAG/Vector search
Mobile SDKs
That said, we're working with early users to really drive prioritization based off of real use cases!
And, we want to continue to add functionality to our self-service dash so that you can "upgrade" your AI without having to modify your source or redeploying.
@mark_watson_28 @sneh_shah Thanks for the feedback! Would love to hear how you'd prioritize the additional features you mentioned
FlowBot
Really cool, Mark 👏 Love how you’re making it easier to skip the backend hassle, super valuable
Excited to see you expand cross-platform, mobile could be a game changer
@papa_iba_sall thanks! We think so too and it's at the top of our list! Expect it soon 😃
Attrove AI
Super slick way to cut backend hassle. How are you thinking about enterprise readiness (e.g. SOC 2) as teams scale on Airbolt?
@monzures it's something that we've considered but isn't a current top priority just based on our current users and their use cases. That said, we're constantly learning and reprioritizing. There's nothing preventing us.
So Airbolt honestly feels like it was built for anyone who’s ever tried to do some quick AI project and immediately hit a wall. You know that moment where you wanna plug in OpenAI and get some vibes going, but suddenly you’re in backend hell—something you did not sign up for, and it totally kills your flow. But with Airbolt, you just sign up, add their SDK, and fire off API calls right from your app frontend, like, “okay, let’s actually ship something tonight” kind of fast.
The security stuff is actually legit and doesn’t feel heavy-handed. They do short-lived JWTs and keep your provider keys locked down, plus IP throttling and origin allowlists so no one messes up your repo or blows your API budget. You don’t see secrets leaking everywhere, which is usually why I’m sketched out by frontend AI work—this is literally safe by default and it doesn’t get in your way. Plus it’s got that thing where you can switch between AI models and provider configs—like, live, with a dashboard, no redeploy, no more “hey we have to push a new build just to change a prompt.” That’s super clutch if you’re experimenting, doing some quick hackathon demo, or rolling out updates for a bunch of random plugins and extensions.
Honestly, it’s wild how you don’t need a backend for rate limits or abuse controls. Airbolt just absorbs that pain—per-user tokens, spend caps, so trolls can’t spike your bill while you’re vibing. And I’m hype about the vendor-neutral part. Switch OpenAI out for Anthropic or whatever comes next, all config-based, plus failover on deck. So you’re not locked into one model and you don’t have to argue with your cofounder about migrating APIs every two months.
Airbolt’s ideal for anyone doing AI stuff but not full-stack heavy: micro-SaaS peeps, product managers, Chrome and Discord bot builds, quick MVPs, or those experimenting with random ideas at 2 AM and want it live, not just sitting in a folder. Extension devs especially get how much it sucks to manage keys and infra—Airbolt gets rid of that stress. And it’s kinda fun to just drop in a React chat and see something work without spending all night on boilerplate, permissions, and worrying about whether the API key is public somewhere.
The open-source part is cool—like, the repo is active, the team actually responds, and the contributor energy matches that indie dev life. Feels like it’s being built in real-time with people using it for actual projects, not just for “enterprise pipeline” stuff. There’s not this big formal barrier; you can just jump in and the tool feels flexible enough to meet what you’re doing, however random. So yeah—it’s clean, it’s safe, doesn’t lock you down, does what you want right when you ask for it, and is clearly made for builders who vibe and iterate instead of planning in long sprints. You can test, swap models, pivot use cases, and keep secrets secret, all while shipping stuff fast. Not much more you can ask for when you just wanna ship and let the LLMs do the heavy lifting