We present a platform technology encompassing a family of innovations that together aim to tackle key challenges with existing implantable brain machine interfaces. The ENGINI (Empowering Next Generation Implantable Neural Interfaces) platform utilizes a 3-tier network (external processor, cranial transponder, intracortical probes) to inductively couple power to, and communicate data from, a distributed array of freely-floating mm-scale probes. Novel features integrated into each probe include: (1) an array of niobium microwires for observing local field potentials (LFPs) along the cortical column; (2) ultra-low power instrumentation for signal acquisition and data reduction; (3) an autonomous, self-calibrating wireless transceiver for receiving power and transmitting data; and (4) a hermetically-sealed micropackage suitable for chronic use. We are additionally engineering a surgical tool, to facilitate manual and robot-assisted insertion, within a streamlined neurosurgical workflow. Ongoing work is focused on system integration and preclinical testing. I. INTRODUCTION Brain Machine Interfaces (BMIs) have a genuine opportunity to effect a transformative impact on both medical [1], [2] and non-medical [3] applications. More specifically, clinical translation can lead to the restoration of movement and communication in patient populations with tetraplegia, amylotrophic lateral sclerosis, locked-in-syndrome, and speech disturbances. Current translational efforts utilize implantable medical devices (IMDs), e.g. Medtronic PC+S [1], experimental neuroscience tools, e.g. Blackrock Neuroport [2], or engineer new devices leveraged on IMDs [4], [5]. A. Key Challenges The major technical challenges with state-of-the-art BMI technology are chronic reliability (device longevity, recording stability, calibration/training) and scalability (extending number of recording and/or stimulation sites). In tackling these, wireless capability is crucial, but brings on its own set of challenges (wireless transfer efficiency, data throughput).