The NPU is in
your Camera.
The AI application isn't.
MountAIn Onboard helps teams deploy trained models inside an existing hardware and software stack. Keep the board, sensors and product architecture that are already decided. Resolve the model, memory and integration work that stands between them and useful on-device intelligence.
Many product teams do not begin with a blank sheet.
The board has been selected. The device is in market or close to it. Sensors, firmware, security and manufacturing decisions are already connected to the platform. Replacing the hardware to accommodate a model creates cost, delay and product risk.
AI integration inside the selected envelope.
Works inside the selected envelope
Assess the model against the memory, compute, power and software constraints of the existing product.
Optimises the
application path
Address the model together with the pre-processing, post-processing and data movement required by the use case.
Preserves the
surrounding engineering
Integrate through the target toolchain and product architecture instead of asking the team to rebuild around a new general-purpose platform.
Creates a route
to validation
Make assumptions, constraints and success criteria explicit so technical teams can test the result in the product context.
Onboard is designed for:
- Camera and imaging products
- Sensors and connected devices
- Equipment with an established embedded platform
- Teams replacing an underperforming or impractical AI approach
- Product lines that need a repeatable path across models or variants
The engagement path
Define the product use case and the decision the model must support.
Review the model, target, memory envelope and current software path.
Identify the technical blockers and the smallest useful proof.
Optimise and integrate against agreed acceptance criteria.
Validate in the product environment before discussing production scope.
A useful first conversation needs only:
Do not send confidential files through the public form. A secure exchange can be arranged after the initial review.
- The model or model family
- The selected hardware and toolchain
- The relevant sensors or input path
- The product constraint that is blocking progress
- A measurable success condition