Company patents
Rain Neuromorphics Inc.
Rain Neuromorphics Inc. exhibits a surprising shift in its patent strategy, moving away from its foundational Machine Learning & AI, which constitutes 50.0% of its portfolio but saw a significant decline of -72.7% in 2025 and no patents so far in 2026. Instead, the company is rapidly emerging in Computer Hardware Architecture, with a substantial 71.4% year-over-year growth in 2025, now representing 45.5% of its portfolio, indicating a pivot towards hardware-centric innovation.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
44 US filings (since 2023) · 9 categories · 8 themes
Novel hardware designs and processing pipelines tailored for specific computational tasks, such as graphics rendering, neural network operations, or matrix transformations, often involving custom circuits, memory arrays, or data flow mechanisms.
Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.
Focuses on the physical design, materials, and manufacturing processes for individual memory cells, including transistor structures, interconnects, and multi-layered (3D) architectures to enhance density and performance.
Hardware and control techniques for optimizing memory access latency, ensuring data integrity, and managing storage resources efficiently. This includes error correction, read/write voltage control, and intelligent data placement or in-memory computation.
Design and implementation of non-traditional logic gates or memory elements, often leveraging new materials or device physics to achieve multi-functionality, adaptive thresholds, or higher density.
Development of memory cells utilizing resistive switching or phase-change materials, including novel material compositions, multi-layered structures, and integration with selector devices like bipolar junction transistors, to achieve non-volatile storage.
Design and fabrication techniques for magnetoresistive random-access memory (MRAM) cells, focusing on magnetic tunnel junction (MTJ) stack profiles, electrode configurations, and dielectric encapsulation to improve performance and reliability.
Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.
Patents
Showing 1-4 of 4
Magnetic Random Access Memory Structures