PicoAI™ is an edge-native artificial intelligence technology designed specifically for embedded systems.
In this video interview, Grant Goris (Boon Logic) and Semir Haddad (MicroEJ) discuss how PicoAI, integrated with MicroEJ VEE, enables embedded devices to learn continuously in real time – directly at the edge – without cloud dependency, neural networks, or specialized AI hardware.
“Introducing PicoAI to the embedded market allows customers to train individualized models in real-time at the edge, which is not achievable with neural network approaches. The integration of Boon Logic’s Nano with MicroEJ VEE brings industry leaders an unprecedented ability to accelerate the delivery of edge-native AI across their portfolios.”
Grant Goris – CEO, Boon Logic
PicoAI brings powerful self-learning capabilities directly to embedded devices, training each device against its own real operational data with minimal CPU usage. By learning what “normal” looks like locally, PicoAI can identify anomalies and usage patterns up to 1,000 times faster than traditional approaches, with precision – even in dynamic and unpredictable environments.
Unlike conventional edge AI solutions, PicoAI does not rely on the cloud, neural networks, AI accelerators, or pre-trained models, making it particularly well suited for constrained, secure, and latency-sensitive embedded systems.
Integrated with MicroEJ VEE, PicoAI can be deployed as part of a modular software architecture, making it easier to scale self-learning AI across device portfolios and evolve capabilities over time.
See PicoAI running on MicroEJ VEE Energy in this demo, showcasing several smart grid use-case.
Embedded devices can now learn and adapt in real time – without cloud connectivity or neural network models!
Looking to add edge-native AI that adapts in real time, scales across product lines, and runs on constrained hardware? Contact MicroEJ to explore how PicoAI and MicroEJ VEE can accelerate your AI-enabled embedded roadmap.