The u-blox ALMA-B2 module family, built on Nordic Semiconductor's nRF54LM20B, ships BLE 6.0, Thread, Zigbee, Matter, and a dedicated Axon NPU in a single pre-certified package. The NPU runs ML inference 15x faster and at lower power than the Cortex-M33 application core alone. The module is globally certified, meaning teams skip the regulatory re-spin that would come with designing the nRF54LM20B directly onto a custom PCB.
The constraint being removed is the three-chip BOM that has been the default for ML at the wireless edge: an MCU for connectivity, a separate AI accelerator for inference, and a PMIC to manage the power profile across both. The nRF54LM20B consolidates all three functions at the die level. The ALMA-B2 certifies that integration as a drop-in module. For industrial IoT teams shipping anomaly detection in motor drives, predictive maintenance in HVAC, or gesture recognition in building automation, the design question shifts from "how do we integrate an AI chip" to "how do we write the model."
The timing is meaningful. Nordic released the nRF54LM20B spec in January 2026; u-blox has the certified module shipping by May. That is a four-month integration and certification cycle. Edge AI hardware is moving fast enough that the module-to-market cycle is now measured in quarters rather than years. Teams that were waiting for a certified, programmable, wireless-plus-ML module no longer have an excuse to defer the design.