Inspiration
Action-camera videos capture the excitement of a ride or workout, but they often miss the data behind the experience. We created DataLayer Studio to combine video with FIT telemetry—such as speed, heart rate, cadence, power, altitude, and GPS—and turn raw footage into a clear, data-rich story.
What it does
DataLayer Studio is a native app for macOS, iPadOS, and iOS. It lets users:
- Import videos and FIT files
- Synchronize telemetry with video
- Create customizable data overlays
- Preview changes in real time
- Export finished videos or transparent overlays
- Preserve alpha transparency for professional editing workflows
How we built it
We built DataLayer Studio primarily with Swift, using SwiftUI for the interface and AVFoundation for video processing.
The project separates FIT parsing, telemetry interpolation, timeline synchronization, rendering, and video export from the platform-specific interface. This allows the same core technology to support both desktop and mobile experiences.
GPT‑5.6 provided significant help during development. We used it to trace complex Swift and SwiftUI flows, investigate cross-platform issues, review export logic, and turn product ideas into small, testable changes.
Challenges we ran into
One of the biggest challenges was accurately synchronizing telemetry with video recorded by different devices. We also had to handle missing data, interpolate values smoothly, process video frame by frame without excessive memory usage, and preserve transparency during export.
Supporting multiple Apple platforms introduced another challenge: improving the iPadOS and iOS experience without causing regressions in the existing macOS app.
Accomplishments that we're proud of
We are proud that DataLayer Studio can transform raw workout data into polished visual overlays while remaining approachable for everyday users.
We are also proud of its native performance, customizable layouts, transparent export workflow, and shared architecture across macOS, iPadOS, and iOS.
What we learned
We learned that reliable media software involves much more than drawing graphics over video. Timing precision, interpolation, memory usage, file compatibility, platform behavior, and export correctness all matter.
We also learned the value of making small, verifiable changes. GPT‑5.6 helped us reason through unfamiliar APIs, identify root causes, and avoid unnecessary complexity.
What's next for DataLayer Studio
Next, we plan to improve the mobile editing experience, add more overlay styles, expand telemetry compatibility, and make synchronization even easier.
Our goal is to help more athletes and creators turn their activity data into videos that are informative, personal, and enjoyable to watch. 🚀
Log in or sign up for Devpost to join the conversation.