Show HN: ServerlessAI – Build, scale, and monetize AI apps without back end (serverlessai.dev)
I’ve always loved building frontend-only apps—those you can prototype over a weekend, host for free on GitHub Pages, and scale to millions of users. Unfortunately, AI-enabled apps complicate things, as exposing your OpenAI key to the world is obviously a no-go. This also means mobile developers often have to run their own servers.
That’s why I built ServerlessAI, an API gateway that lets you securely call multiple AI providers directly from client side using OpenAI-compatible APIs. You can authenticate users through any identity provider, like Google or Apple, and set per-user request or spending quotas. You can also define an allowlist for endpoints and models. To monetize, you can apply different quotas for various user tiers.
To start, I recommend checking out our tutorials, where we walk you through building a complete, deployment-ready AI app in 5 minutes. We’ve got tutorials for React, Next.js, and iOS: https://serverlessai.dev/docs/tutorials/
Our long term vision is to offer the best toolkit for AI developers at every stage of their project’s lifecycle. If OpenAI / Anthropic / etc are AWS, we want to be the Supabase / Upstash / etc. We are building optional out-of-box tools for authentication and payment management, so you can roll out your prototype faster. In the future, we want to provide the best prompt engineering tools for fine-tuning, A/B testing, and backtesting, as well as the best observability tools.
We’d love to hear your feedback. Thanks for stopping by!
31 comments
[ 0.26 ms ] story [ 77.5 ms ] threadOne challenge on frontend-only apps is if the prompt is proprietary then this will be exposed unless you will then offer prompt templating or prompt mapping on your side i.e. the frontend says prompt: Template_123 and then this maps to the actual prompt somehow. Prompting is important still and maybe for a while so having the internals externally available could be sensitive.
I’d also recommend they clean up the copy of what they offer (expand on the why).
Other than that looks cool
If pricing is preventing anyone from using our product, please shoot me an email (in my HN profile) and we'd love to hear about your use case!
Good call on the marketing copy! We will do some revisions!
I know that might sound like putting the server back to serverless. But I would say it's being your own serverless provider - once you have the platform installed on your servers you can build frontend-only AI apps on top.
Hope you don't mind the self-plug. Your approach definitely a ton of advantages when starting out (no infra to manage etc).
(And yes, I hate their name too. I don't honestly know how defendable an entire technology term actually is. It also results in terrible Googling.)
"ServerlessAI" and "serverlessai.dev" shouldn't be infringing because they incorporate the generic term in their mark, not the Serverless Framework-specific term. Of course, this means that ServerlessAI would have the same issues you point out - a less-defensible mark and poor Google results.
Also, in the US pretty much anyone can sue for anything, so even if you're in the right it can be an expensive headache to have to defend yourself.
I would also build this on top of firebase marketplace: https://extensions.dev
Will look into Firebase Marketplace! That is a great suggestion!
How is it different from Puter AI, which offers auth + free inference?
https://docs.puter.com/AI/chat/
Looking at Puter's offering, at the end of the day, we serve the same goal of making developer's life easier. ServerlessAI is more narrowly focused on AI use cases, while Puter is providing a more generic app runtime. Both have their best use cases!
(I suppose, relately, I have trouble understanding why anyone would just sort of presume OpenAI would be forever the best backend here as well?)
And you are right on the money that OpenAI may not be the best backend forever. That's why we also support Anthropic, Groq, and Mistral.
There's lots of novelty apps atm that, as the other commented stated, just want to get to market as soon as possible to validate an idea
Biggest use case seems to be for people who want to prototype something quickly, they don’t yet want to bother with managing the infra and don’t mind the extra cost since this will be running at small scale. But if the experiment is successful, then the customer churns as it (most of the time) makes little sense to scale ML on serverless. And if the experiment is not successful, they are obviously also going to churn.
> You can authenticate users through any identity provider, like Google or Apple, and set per-user request or spending quotas. You can also define an allowlist for endpoints and models. To monetize, you can apply different quotas for various user tiers.
I really wish companies and people would stop saying things like this. “Focus on what’s important,” “focus on product,” etc. It’s frankly insulting to the admittedly small percentage of tech who deeply understand and care about the infrastructure that makes all of this magic possible.
If someone isn’t managing servers, your serverless magic will not work. If someone isn’t managing DBs, your product will not work. There is no getting around this problem; at some level, someone has to know how computers actually work, and to defend them against the abuses levied by people who neither know nor care to learn.
The latest one I recall was something like, “we’ll be sure to use the real medicine instead of the placebos.”