Tiny ML

At Fortifyedge we accept all great challenges. This one was just particularly Tiny. 

What is Trust and how can we build it from the ground up within a Zero trust model that operates within a denied environment?

The answer was TinyML running on embedded systems with unique memory management and sensor fusion. Our TinyML methods and models enabled us to deploy multiple algorithms on an M4 through to M7 with custom ML being created and deployed on an M0.


Tiny MLOps

Our process

The adoption and then adaption of MLOps to Tiny MLOps allow us to test learn and continuously deploy. For the warfighter, we also include H4D so we understand your problem mission fit. For commercial customers, we utilise value proposition and BMC to understand your user pain and gain points. Together these discovery methods make sure we work with you to discover and deliver tiny but powerful solutions continuously through to your teams and customers.

We have built our Bird's eye view and Bird of Prey platforms to take advantage of the sensor data and mission context. By using explainable AI we ensure you understand what's happening on the mission so you can implant your wisdom in the decision.

Designed with input from critical infrastructure operators, The insights gained allowed us to develop models that speed up contextual decision making by removing noise and building operator trust in the AI. 

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Peter Padd: Aus 61.433.919.731
                 USA 1.669.800.7634