developers worldwide face the deployment gap between trained model and real device.
EDGE STUDIO
AI hardware deployment in minutes, not weeks.
Bring your data and your device. Edge Studio trains, compiles, optimizes, and deploys your trained model onto your device - without writing a single line of code.
THE GAP
Models that never leave the laptop.
A trained model is the easy half. Getting it onto real hardware means toolchains, cross-compilation, memory limits, and driver quirks - a wall between the ML world and the embedded one.
of engineering effort to make one model run on one target board.
HOW IT WORKS
Three steps. Zero configs.
You handle the two things only you can - your data and your device. Edge Studio handles everything in between.
01
You bring your data and your device
Pick your use case, select your target board, and upload your dataset.
02
Edge Studio handles the hard part
Train, optimize, and compile for your exact hardware with no embedded toolchain work.
03
Your model runs on real hardware
Live inference on-device with fast iteration in minutes, not months.
WHO IT IS FOR
Built for both sides of the gap.
ML engineers
You trained it. Now ship it, without falling into embedded toolchains and board-level friction.
Embedded engineers
You know the hardware. Edge Studio adds AI workflow depth without forcing a full ML stack pivot.
Students and researchers
Focus on ideas, model quality, and experiments instead of deployment plumbing.
WHY EDGE STUDIO
Independent by design. Sovereign by default.
Independent
No lock-in and no vendor agenda. Open standards across supported hardware, frameworks, and use cases.
Seamless
One flow, zero configs: connect device, upload data, train, deploy.
Data sovereignty
Managed cloud, private cloud, or full on-premise deployment under your own control.
READY WHEN YOU ARE
Your model. Your device. Minutes from now.
Edge Studio is live today. Start deploying at edgestudio.ai.