Android Text-to-Video Platform Build
Budget: ₹12,500 – ₹37,500 INR
I’m ready to launch a combined web platform and dedicated Android app that turns plain text into fully rendered videos. The core feature is an AI-driven text-to-video engine—think “enter a script, receive an MP4”—integrated seamlessly across both the browser and the mobile experience.
Scope
• Website: responsive front end, secure user accounts, dashboard to submit text, preview clips, download or share finished videos.
• Android app: mirrors the web functionality with smooth performance on current OS versions; Play-Store-ready build and listing assets are part of the hand-off.
• AI engine: you may plug in an existing model (e.g., Stable Video Diffusion, Runway, or a custom TensorFlow/PyTorch pipeline) or propose an API solution, but latency and output quality must stay competitive.
• Admin panel: user management, job queue monitoring, and storage controls.
• Data work: an initial dataset must be entered manually into the system—roughly a few thousand rows—and cross-checked for accuracy. Manual data entry and data validation are therefore essential components of the job.
Acceptance criteria
1. Text submitted on either platform reliably returns a downloadable video with sound and 720p+ resolution.
2. Android build passes Play Console review without warnings.
3. All manual entries match the supplied source sheets; spot checks will be performed.
4. Source code, build scripts, and a brief deployment guide are delivered in a Git repository.
If you have a track record with Android Studio, modern JS frameworks, and experience wiring AI inference pipelines to real-time user interfaces, I’d like to see what you can bring to the project.
Scope
• Website: responsive front end, secure user accounts, dashboard to submit text, preview clips, download or share finished videos.
• Android app: mirrors the web functionality with smooth performance on current OS versions; Play-Store-ready build and listing assets are part of the hand-off.
• AI engine: you may plug in an existing model (e.g., Stable Video Diffusion, Runway, or a custom TensorFlow/PyTorch pipeline) or propose an API solution, but latency and output quality must stay competitive.
• Admin panel: user management, job queue monitoring, and storage controls.
• Data work: an initial dataset must be entered manually into the system—roughly a few thousand rows—and cross-checked for accuracy. Manual data entry and data validation are therefore essential components of the job.
Acceptance criteria
1. Text submitted on either platform reliably returns a downloadable video with sound and 720p+ resolution.
2. Android build passes Play Console review without warnings.
3. All manual entries match the supplied source sheets; spot checks will be performed.
4. Source code, build scripts, and a brief deployment guide are delivered in a Git repository.
If you have a track record with Android Studio, modern JS frameworks, and experience wiring AI inference pipelines to real-time user interfaces, I’d like to see what you can bring to the project.