low-power-ai
(5)
CyberSwarm Inc.
CyberSwarm is a neuromorphic engineering company building brain-inspired, memristor-based hardware that lets machines learn and adapt locally, at the edge, without the cloud. Founded in 2017 by Mihai Raneti and headquartered in San Mateo, California with R&D roots in Ploiesti, Romania, the company is developing a neuromorphic System-on-a-Chip for cybersecurity and energy-efficient AI, positioning its architecture as a new computational layer between conventional digital systems and quantum computing. In May 2026 it raised a $50 million Series A to scale toward commercial deployment across automotive, aerospace, defense, healthcare and robotics.
DEEPX
DEEPX is a South Korean fabless semiconductor startup building ultra-low-power neural processing units (NPUs) for on-device and edge AI. Founded in 2018 by former Apple chip designer Lokwon Kim, the company designs AI accelerators - led by its 25 TOPS DX-M1 chip - that run vision and generative AI models at under 5 watts, aiming to move intelligence out of the data center and into robots, cameras, factories, mobility and everyday devices. It raised an $80.5M Series C in 2024 at a $529M valuation and positions itself as a 'Physical AI infrastructure company.'
ModelCat AI
ModelCat AI, formerly the low-power chip pioneer Eta Compute, builds an agentic, hardware-aware platform that automatically designs, trains, optimizes and validates machine-learning models for embedded, edge and IoT devices. Its patented AI-in-the-Loop workflow, backed by a physical hardware farm that calibrates results against real silicon, compresses a model-development cycle that once took 12 to 24 months down to a matter of days. The Sunnyvale company works with chipmakers including NXP and Alif Semiconductor to hand developers ready-to-run models tuned to the exact constraints of the hardware they will run on.
Applied Brain Research
Applied Brain Research (ABR) is a Waterloo, Ontario AI hardware company spun out of the University of Waterloo's Centre for Theoretical Neuroscience. It builds brain-inspired chips and software that run real-time AI - full-vocabulary speech recognition, text-to-speech and sensor processing - directly on edge devices at power levels measured in milliwatts. Its patented state-space models and the Legendre Memory Unit power the TSP1 Time Series Processor, which ABR calls the world's first single-chip solution for full-vocabulary speech recognition, doing the work of cloud voice AI while consuming 10 to 100 times less power.
EnCharge AI
EnCharge AI is a Santa Clara semiconductor startup, spun out of Princeton University, building AI accelerator chips based on analog in-memory computing. Its charge-based architecture runs heavy AI workloads on laptops, workstations and edge devices at roughly 20x the energy efficiency of conventional GPUs. Its first product, the EN100 accelerator, delivers 200+ TOPS within an 8.25W power budget, aiming to move generative AI out of the data center and onto the devices people actually hold.