AI-Powered Mobile Video Editor
Budget: $30 – $250 CAD
I want to take the core idea behind VIIDURE and elevate it into a truly professional-grade editor for iOS and Android, driven by smart, on-device AI. The finished apps should feel fast and polished, able to slot straight into a filmmaker’s daily toolkit rather than a casual creator’s toy.
Key features to build in:
• Auto-editing: the app should analyse footage, detect highlights, trim dead space and produce a first-pass cut without user input.
• Facial recognition: automatically tag people across clips so users can filter, search and build sequences around specific faces.
• Voice recognition: transcribe dialogue in real time, attach captions to the timeline and make the text searchable for quick clip selection.
Core expectations
– Native performance and native UI on both platforms (Swift/SwiftUI for iOS, Kotlin/Jetpack Compose for Android, or a robust cross-platform alternative if it truly matches native feel).
– A professional interface: multi-track timeline, keyframing, colour tools, export presets up to 4K.
– Cloud-free operation for the AI tasks; everything should run on device to keep editors working offline and to protect their footage.
– Clean, modular codebase with unit tests and concise documentation so future developers can extend it.
Acceptance criteria
1. A TestFlight build and an Android internal test build demonstrating the three AI features working end-to-end on sample footage.
2. A short demo video showing the editing workflow from import to export.
3. Repository access with a clear README covering project setup, build steps and a high-level architecture overview.
Deliver these milestones and we will move straight into beta-testing and feature expansion.
Key features to build in:
• Auto-editing: the app should analyse footage, detect highlights, trim dead space and produce a first-pass cut without user input.
• Facial recognition: automatically tag people across clips so users can filter, search and build sequences around specific faces.
• Voice recognition: transcribe dialogue in real time, attach captions to the timeline and make the text searchable for quick clip selection.
Core expectations
– Native performance and native UI on both platforms (Swift/SwiftUI for iOS, Kotlin/Jetpack Compose for Android, or a robust cross-platform alternative if it truly matches native feel).
– A professional interface: multi-track timeline, keyframing, colour tools, export presets up to 4K.
– Cloud-free operation for the AI tasks; everything should run on device to keep editors working offline and to protect their footage.
– Clean, modular codebase with unit tests and concise documentation so future developers can extend it.
Acceptance criteria
1. A TestFlight build and an Android internal test build demonstrating the three AI features working end-to-end on sample footage.
2. A short demo video showing the editing workflow from import to export.
3. Repository access with a clear README covering project setup, build steps and a high-level architecture overview.
Deliver these milestones and we will move straight into beta-testing and feature expansion.