OnSpace AI Pricing: How Credits Work and Where to Get 500 Free
OnSpace AI runs on a credit-based pricing model. Here's how credits work, what they pay for, and how to redeem 500 free credits.
What is OnSpace AI and how does its pricing work?
OnSpace AI is a no-code platform that builds mobile apps, web apps, and AI agents from natural language prompts. Instead of a flat monthly fee for a fixed set of features, it runs on a credit system: you spend credits as the AI generates code, wires up databases, connects AI models, or publishes your app to a store. New users can also claim 500 free credits through a redemption code, which is enough to test the platform before spending real money on it.
TL;DR
- OnSpace AI uses a credit-based pricing model rather than a flat subscription, so usage (prompts, builds, fixes) draws down a credit balance instead of enabling a fixed feature tier.
- New accounts can claim 500 free credits by signing up through the platform, going to account settings, and entering a redemption code.
- The platform bundles AI model access into the credit cost, so you don’t need to buy separate API keys from OpenAI or Anthropic or stand up your own backend to hide them.
- A built-in database and authentication system are part of what credits pay for, replacing the need for a separate Supabase or Firebase setup.
- A runtime scanner catches bugs across features automatically, which cuts down on wasted credits spent re-explaining errors to the AI.
- Publishing to app stores or generating an APK is included in the workflow, turning what’s normally a multi-day technical process into something that finishes in minutes.
- Monetization tools like in-app purchases (via RevenueCat) or Stripe are supported, so credits also cover the work of building a paywall, not just the base app.
Everyone else built a construction worker.
We built the contractor.
One file at a time.
UI, API, database, deploy.
How does the credit system actually work?
Every action inside OnSpace, from the initial prompt that scaffolds an app to follow-up requests like “add a sign-up screen” or “lock this feature behind a subscription,” consumes credits. The exact credit cost per action wasn’t detailed in the walkthrough, but the general model is straightforward: you chat with the AI to describe what you want, it generates the code and infrastructure behind the scenes, and that work draws from your balance.
This matters because OnSpace isn’t just generating static code. When it builds an AI chat feature, for example, it’s also connecting your app to a hosted AI model without you needing to supply an API key. That convenience (skipping the OpenAI or Anthropic signup, the backend to protect the key, the rate-limit handling) is part of what the credit spend is paying for. In a traditional dev setup, model access is billed separately and configured manually. Here, it’s rolled into the same credit pool that pays for everything else the AI does.
What do the 500 free credits actually cover?
The free credit offer is aimed at letting a new user go from idea to working prototype without paying anything upfront. Based on the build shown in the demo, a reasonably complete app, one with a chat interface, a quiz feature, a progress tab, sign-up and login, a real backend database, and a payment paywall, took about 20 minutes of prompting to construct. If that kind of build fits within a 500-credit allowance, it suggests the free tier is generous enough to actually finish a functional app, not just poke at a demo sandbox.
To claim the credits, the process is:
- Sign up for an OnSpace account.
- Go to account settings.
- Enter the redemption code.
- Credits are added to the account instantly.
There’s no separate approval step or waiting period mentioned. It’s a straightforward self-serve redemption.
Why does OnSpace charge for AI model access instead of requiring your own API key?
Most no-code tools that let you add “AI features” to an app expect you to bring your own OpenAI or Anthropic API key. That means creating accounts with those providers, generating keys, and building a backend server whose entire job is to hide that key from the client so it doesn’t get stolen or abused. It’s a meaningful chunk of technical setup even for people who already know how to code.
OnSpace folds model access into its own credit system instead. You describe the AI behavior you want in plain language (“the AI should reply naturally, correct mistakes, and explain corrections”), and OnSpace handles calling the underlying model and returning a response inside your app. You’re not managing rate limits or key rotation. The tradeoff is that you’re paying OnSpace’s credit rate for that access rather than a model provider’s raw API rate, which is the standard tradeoff with any platform that abstracts infrastructure away from you.
Is OnSpace AI worth the cost compared to building it yourself?
For someone with no backend experience, the calculation isn’t really about credit cost versus API cost. It’s about credit cost versus the cost of learning (or hiring for) authentication systems, database schema design, payment integration, and app store submission. Publishing a React Native app manually involves Expo build configuration, submission documentation, certificates, and provisioning profiles, a process that’s genuinely difficult without prior mobile dev experience. OnSpace compresses that into a background process that reportedly takes 10 to 15 minutes.
For someone who already knows how to code and just wants raw API access at wholesale rates, paying a platform for bundled model access may not be the cheapest path. But for solo builders, indie hobbyists, or anyone prototyping an idea before committing engineering time to it, trading a credit balance for a working app with a database, login flow, and paywall already wired up is a reasonable exchange, especially with 500 free credits available to test the waters first.
What else is included beyond app generation?
A few things bundled into the OnSpace workflow are worth knowing about since they affect how far your credits go:
- Runtime scanner: rather than manually hunting for bugs and describing them to the AI, you click through your app’s screens with the scanner active, and it detects and can auto-patch errors it finds. This reduces the back-and-forth (and credit spend) that normally comes with debugging AI-generated code.
- Built-in database: user records, chat history, and other app data live in a dashboard you can inspect directly, without connecting to Supabase or Firebase separately.
- Payment integration: in-app purchases via RevenueCat or payments via Stripe can be added by prompt, with tutorials available on OnSpace’s official YouTube channel, which the creator notes is updated weekly.
- Publishing: APK downloads for Android testing are near-instant, and app store submission is handled as an automated background process.
All of these draw from the same credit pool, so the practical cost of a project depends on how many features and iterations it needs, not just how complex the initial prompt is.
Frequently Asked Questions
How do I get the 500 free OnSpace AI credits?
Sign up for an account on the OnSpace platform, open account settings, and enter the redemption code. The credits are added to your account immediately with no waiting period.
Does OnSpace require me to bring my own AI API keys?
No. OnSpace provides access to a library of AI models directly through its platform, so you don’t need to create accounts with providers like OpenAI or Anthropic or manage your own API keys and backend infrastructure.
What happens if my free credits run out?
The transcript doesn’t detail specific paid credit packages or renewal pricing. What’s confirmed is that the platform runs on a credit-based system where actions like prompting, fixing bugs, and publishing consume credits from your balance.
Can I publish an app built with OnSpace to the App Store or Google Play?
Yes. The platform supports one-click publishing to app stores and instant APK generation for Android testing, cutting out the manual certificate and provisioning profile work normally required.
Do I need coding experience to use OnSpace AI?
No. The entire workflow shown is prompt-based: you describe features in natural language, and the AI handles code generation, database setup, authentication, and payment integration without requiring you to write code directly.