Embedded AI & Engineering: Edge ML, IoT, Firmware | micara
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micara Embedded AI - Seven capability pillars
Technology · Pillar

Embedded AI & Engineering

Where artificial intelligence meets tangible reality. We design, build and ship intelligent systems, from the microcontroller to the training cluster, from proof of concept to profit.

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What we do

Edge Machine Learning

ML models that run where the data is created, on microcontrollers, sensors and gateways. Quantization, TinyML, on-device inference and the tooling around it.

IoT Development

End-to-end connected products: firmware, sensing, connectivity, cloud integration and fleet management, a dynamic duo of AI and IoT shaping smarter systems.

Feasibility Studies

Before you invest: can it be built, what will it cost, what are the risks? Rapid prototyping and honest engineering assessments that de-risk your decision.

Engineering depth that carries into advisory

Because we build AI systems from the ground up, we can realistically assess compute demand, GPU depreciation cycles, workload profiles and technology risk, the assumptions that make or break a data-center financial model. That engineering depth is what classical M&A advisors lack.

Transaction & Technology Advisory Article: What Investors Miss About AI Compute

Have an embedded AI or IoT project in mind?

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