How to Add AI Video Generation to Your Mobile App: A Developer's Guide
Imagine: a user clicks 'Generate Video' and gets a ready clip in the app within a minute. But in reality, models like Runway Gen-3, Sora, Kling require powerful GPUs (A100/H100) and take 30 seconds to several minutes. The mobile developer's task is to set up an async flow so the user doesn't leave while waiting. We integrate these APIs into your iOS/Android app, ensuring reliable generation, caching, and notifications.
How to Integrate Runway API into a Mobile App?
Runway provides a REST API with polling for status checks. On iOS, we implemented a service with async/await and a progress bar that simulates execution based on typical generation time. On Android, we use WorkManager with CoroutineWorker—the task runs in the background even when the app is minimized. Here's an example iOS service:
class VideoGenerationService { func generate(prompt: String, sourceImage: UIImage?) async throws -> URL { let taskId = try await runwayClient.createTask( prompt: prompt, imageURL: sourceImage.map { try await uploadImage($0) }, duration: 5, ratio: "1280:768" ) UserDefaults.standard.set(taskId, forKey: "pendingVideoTaskId") return try await pollWithBackoff(taskId: taskId) } private func pollWithBackoff(taskId: String) async throws -> URL { let intervals: [TimeInterval] = [3, 5, 8, 10, 10, 15, 15, 20, 20, 30] for interval in intervals + Array(repeating: 30.0, count: 10) { try await Task.sleep(nanoseconds: UInt64(interval * 1e9)) let task = try await runwayClient.getTask(id: taskId) switch task.status { case .succeeded: UserDefaults.standard.removeObject(forKey: "pendingVideoTaskId") return task.output.first! case .failed: throw VideoGenError.generationFailed(task.failure ?? "Unknown") default: continue } } throw VideoGenError.timeout } } On Android: WorkManager with CoroutineWorker is the right choice for long-running background tasks. Polling in doWork(), Result.retry() on PROCESSING, Result.success(outputData) on SUCCEEDED.
What to Do If Generation Takes Longer Than a Minute?
Push notification is a must-have option. The backend tracks task status and sends FCM/APNs on completion. Deep links (Universal Links / App Links) lead to the result screen with auto-play. If the user minimized the app, progress is saved via pendingTaskId in UserDefaults.
Estimating Real Progress Without API Data
Most APIs do not return a percentage—only status PENDING/PROCESSING/SUCCEEDED. We use a simulated progress bar: a timer for 55 seconds (95%), then wait for the actual response. This beats an empty spinner.
AI Video API Comparison Table
| Provider | API | Clip Length | Typical Time | Input Data |
|---|---|---|---|---|
| Runway Gen-3 Alpha | REST + polling | 5–10 sec | 30–90 sec | Text, Image-to-Video |
| Kling AI | REST API | 5–10 sec | 60–180 sec | Text, Image-to-Video |
| Hailuo (MiniMax) | REST API | 6 sec | 45–120 sec | Text, Image-to-Video |
| Luma Dream Machine | REST API | 5 sec | 30–60 sec | Text, Image, Keyframes |
| Replicate (various) | REST + WebSocket | 2–10 sec | 30–120 sec | Depends on model |
Runway API is about 2x faster than Kling AI for typical clips. To choose an API, consider generation time and clip length. Runway API is the most mature with SDKs for TypeScript/Python. Sora from OpenAI is currently only available through a partner program. Compliance with the App Store Review Guidelines (section 4.2) is mandatory for publication.
Comparison of Async Generation Approaches
| Aspect | Polling | WebSocket |
|---|---|---|
| Ease of integration | High | Medium |
| Progress accuracy | Low (status only) | High (step-by-step messages) |
| Server load | Medium (frequent requests) | Minimal (event-driven) |
| Recovery on disconnect | Automatic (re-request) | Requires reconnection |
The choice between polling and WebSocket depends on update frequency and criticality of progress. For simple scenarios, polling suffices; for complex ones, WebSocket.
Common Mistakes in AI Video Integration
- Not handling timeouts: if generation takes longer than expected, the user sees an endless spinner.
- Not saving
taskIdbefore exiting the app: losing progress. - Ignoring API quotas: exceeding limits causes errors.
- Not optimizing caching: re-downloading the video on every entry.
We solve these issues during the design phase.
Deliverables & What's Included
- Analysis: selecting the optimal API for your needs (clip length, budget, quality).
- Integration: implementing the async flow with polling, progress bar, and result caching.
- Background processing: WorkManager/BGTaskScheduler for long tasks.
- Push notifications: FCM/APNs with deep linking.
- Documentation: usage guide and API documentation.
- Access: repository access and credentials for all services.
- Training: up to 2 hours of knowledge transfer for your team.
- Support: 3 months of free post-launch support.
Our Work Process
- Analysis — we study your app, select an API, estimate load.
- Design — architecture of the flow, caching scheme, security.
- Implementation — writing code, integrating SDK, testing.
- Testing — verification on real devices, error simulation.
- Deployment — publication to App Store / Google Play, monitoring setup.
Timeline and Cost
Basic integration (one API, player, cache) takes 5 to 7 days and costs around $3,000 to $5,000. Full flow with background tasks, push, Image-to-Video, and gallery takes 3 to 4 weeks and costs $10,000 to $15,000. The exact cost is calculated individually after reviewing the project.
Our experience integrating AI features spans more than 5 years and 15+ successful projects. We guarantee quality and compliance with the App Store Review Guidelines (section 4.2).
Ready to start? Contact us for a preliminary estimate. Get a consultation on API selection and architecture today.