Edge AI Becomes Concrete – MicroEJ's Full AI Stack for Embedded Devices

Machine learning and generative AI are no longer reserved for powerful cloud servers or high-end hardware. MicroEJ makes Edge AI concrete: flexible, cost-driven, and deployable on virtually any embedded device, including the most resource-constrained silicon.

In this video, discover MicroEJ’s full Edge AI services portfolio: GenAI, MicroAI, and PicoAI.

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Three AI Services. One Platform. Any Hardware.

MicroEJ delivers a complete AI stack designed for embedded systems — from next-generation audio devices to microcontrollers with ultra-small memory footprints. Whatever the silicon, whatever the use case, MicroEJ has an AI solution that fits.

GenAI – Generative AI for Next-Generation Audio Devices

In collaboration with Qualcomm, MicroEJ brings generative AI capabilities to Snapdragon-powered audio devices.

Snapdragon-powered audio that understands you: natural language interaction built for audio hardware
Downloadable apps + cloud intelligence: combine on-device capabilities with cloud services
Adaptive, personalized sound experiences: AI that evolves with the user
Gateway to the “Ecosystem of you”: a new paradigm for connected audio products

MicroAI – Embedded Neural Network Inference on Ultra-Small Silicon

MicroAI™ is a lightweight AI inference engine that brings TinyML capabilities directly to embedded systems, enabling real-time decision-making on microcontrollers with limited memory and compute – no cloud, no external accelerators.

Local decision-making on low-power chips: run ML models entirely on-device
Faster responses and no cloud dependency: reduce latency and eliminate connectivity requirements
Designed for ultra-small silicon constraints: memory-optimized execution for MCUs with as little as a few kilobytes of RAM
Suitable for wearables, appliances, and consumer devices: from health monitoring to gesture recognition

▷ More info about MicroAI

PicoAI – Unsupervised ML for On-Device Learning and Ultra-Fast Inference

PicoAI™ is an edge-native AI engine that learns directly from real-world data, without datasets, labeling, or cloud training pipelines, bringing self-learning intelligence to the smallest microcontrollers.

Learns normal behavior locally: trains continuously against its own real operational data
Detects anomalies and identifies patterns in real time: up to 1,000× faster than traditional approaches
No datasets, no labeling, no training pipeline: zero infrastructure overhead
Runs on MCUs with tiny memory footprints: no AI accelerator required
Suitable for Energy Devices, Industrial Automation, and Consumer Devices

▷ More info about PicoAI

Benefits for Device Manufacturers

MicroEJ’s Edge AI services share a common foundation: a single, unified platform that scales across silicon families and product lines.

Bring AI everywhere, on any device Deploy machine learning and generative AI regardless of hardware constraints, from MCUs to MPUs, at any price point.

Lower cost, lower latency, more privacy On-device intelligence eliminates cloud dependencies, reduces infrastructure costs, and keeps sensitive data local.

Longer device lifecycles via software extensibility Update and extend AI capabilities after deployment, without hardware changes, protecting your investment over time.

One platform scaling across all silicon families A consistent software stack that accelerates development and simplifies maintenance across your entire product portfolio.

Ready to Bring AI to Your Embedded Devices?

Explore how MicroEJ’s Edge AI services (GenAI, MicroAI, and PicoAI) can power your next product generation.

Additional Resources

PicoAi Unsupervised Edge AI

IP Portfolio

PicoAI: Brings Real-Time, Self-Learning AI to Embedded Devices

IP Portfolio

MicroAI: Embedded AI for Smarter Devices, Even on the Smallest Silicon

VIDEO

Demo video: PicoAI, a new approach to Edge AI