01
Works inside constraints
Assess memory, compute, power and software limits of the product.
MountAIn Onboard
Bring intelligence into the product you already have.
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.
Application / camera
When hardware is no longer a choice
Onboard starts from the platform as it is.
The board may be selected and the device close to market. Sensors, firmware, security and manufacturing decisions are already connected. Replacing hardware for a model creates cost, delay and product risk.
What Onboard does
AI integration inside the selected envelope.
02
Optimises the application path
Address model, processing and data movement together.
03
Preserves engineering
Integrate through the existing toolchain and architecture.
04
Creates a route to validation
Make assumptions and success criteria explicit and testable.
A fit for product teams
From cameras to connected equipment.
Onboard supports products with an established embedded platform and teams replacing an impractical AI approach or creating a repeatable route across variants.
- Camera and imaging products
- Sensors and connected devices
- Equipment with an established platform
- Product lines spanning models or variants
Trained model
MountAIn Core
Deployed application
The engagement path.
- 01
Define
Use case and decision.
- 02
Review
Model, target and software path.
- 03
Isolate
Smallest useful proof.
- 04
Integrate
Against acceptance criteria.
- 05
Validate
Inside the product environment.
Keep what already works.
The objective is not to redesign the product around AI. It is to make the chosen intelligence work inside the product already built.