A product photo tool
Upload a real product image, choose a setting, compare the result with the original and keep an approved version. Build around the details sellers need to get right.
Build your own AI media product
Turn a specific customer problem into a repeatable tool: product images, business videos or lesson narration. Give it your own interface, saved projects and a workflow customers understand.
Demos start with prepared briefs and shot suggestions. You choose when to generate; preparing a plan does not spend AI credits.
A seller wants usable product visuals. An educator wants lesson narration. An agency wants an approved clip for a campaign. Start with that result and decide what the customer supplies, what they review, and what they can download. A general chat can help create an asset; your product makes the same useful process easy to repeat.
Upload a real product image, choose a setting, compare the result with the original and keep an approved version. Build around the details sellers need to get right.
Review the business brief, choose a scene direction and generate the clip. Add voiceover and final assembly as explicit steps when your product needs them.
Approve the script, choose a supported voice and save the audio beside the lesson. Let a teacher correct one section without starting the entire project again.
Create pages for inputs, projects and results. Add user accounts and rules for who can see each file. Bubble is a visual app builder that can provide this part; its hosting is separate from the managed AI service.
Install the connector and use the included building skill with a supported AI coding assistant. Define the input form, choose a compatible model, submit a tracked job and retrieve its result. The assistant needs access to your app and editing tools.
Test a real input, waiting state, failed request, page reload and saved output. Review quality before adding more models. If you charge your customers, build their checkout and entitlements separately from your managed AI subscription.
The managed service connects your app to compatible fal generation models, keeps provider credentials on the server, and tracks jobs against a shared app credit allowance. A building skill helps an AI coding assistant adapt the integration to your existing Bubble app. You still choose the product experience, own the customer relationship and review the generated quality.
Search the fal catalog and connect compatible queue inference endpoints through a model ID and model-specific JSON inputs. Running a request requires schema validation, provider access and verified pricing. A catalog listing is not a guarantee that the model can run: models without a supported usage quantity stay unavailable until configured. The service does not promise that every catalog model has been tested.
Realtime sessions, streaming generation and training are separate integrations. A new model may need different input fields and result handling; choosing its name alone does not adapt your interface.
Technical references: fal queue and result documentation · Bubble server-side plugin actions.
One managed plan
$30 in AI credits included.
Plan details & account →Subscription availability is shown on the account page.
Credits reset monthly with no rollover. Your app’s users share its allowance. Eligible requests use verified fal unit prices and supported usage quantities. Credits are reserved before generation and reconciled to actual provider costs afterward, which can take over an hour. Different models and settings use different amounts. There are no automatic overage charges.
Bubble hosting, your AI assistant and any other services your app uses are separate. Review the selected model’s terms for your intended use.
You can begin with a Bubble app you have created or generated, then add the AI workflow. You will still need to review the app’s data, privacy rules and behavior. The building skill provides integration guidance; it does not replace testing your product.
You can build a paid customer experience around your workflow. Your customer checkout, permissions and usage rules need to be implemented in your app. Review provider and model terms for the type of content and commercial use you intend.
One specific output, a small input form, a clear generation status, a quality review and a saved result. Keep model choice optional until you have demonstrated that the default workflow solves the customer’s problem.