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Applied Brain Research

Category: AI Chips / Semiconductors

Applied Brain Research develops neuromorphic AI chips and edge computing solutions, including the TSP1 neural network accelerator chip for low-power, high-performance AI capabilities in battery-powered devices. Applied Brain Research was founded in 2013. The company is led by Kevin Conley. Based in Waterloo, Ontario, Canada. Team size: 11-50. Total funding raised: $3.6 million. Latest round: Seed. Key investors include ["Two Small Fish Ventures","Silicon Catalyst Ventures","Garage Capital","Raptor Group","Fast Forward AI Accelerator","OneEleven"].

Founded
2013
Headquarters
Waterloo, Ontario, Canada
Team size
11-50
Total funding
$3.6 million

Value proposition

Enables natural voice interfaces, bio-signal classification, and real-time AI processing in edge devices through patented low-power neuromorphic computing technology.

Products and solutions

["TSP1 Neural Network Accelerator Chip","Nengo Compiler and Runtime Platform","ABR Reach (robotic reaching application)","Vision and Speech AI Applications","Neuromorphic AI Algorithms (spiking deep learning, reinforcement learning)"]

Unique value

Pioneers Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA) for biologically inspired AI systems, integrating brain-like computation with neuromorphic hardware.

Target customer

Robotics, consumer electronics, automotive, healthcare, and industrial automation industries requiring advanced AI processing with minimal power consumption.

Industries served

["Robotics","Consumer Electronics","Automotive","Healthcare","Industrial Automation"]

Technology advantage

Combines cutting-edge neuroscience research (e.g., Spaun brain model) with proprietary neuromorphic chip design, enabling superior energy efficiency and real-world adaptability compared to traditional AI solutions.

How they differentiate

Applied Brain Research differentiates itself through brain-inspired AI chip architectures optimized for edge computing, emphasizing energy efficiency, real-time processing, and partnerships with academic institutions for neuroscience-driven innovation.

Main competitors

["IBM","Intel","BrainChip","Qualcomm","SynSense"]

Key partnerships

["Intel (Loihi neuromorphic chip collaboration)","Spinnaker and BrainDrop neuromorphic platforms","Academic research institutions for neuroscience advancements"]

Notable customers

["Academic research institutions","Defense contractors (unspecified)"]

Major milestones

["2013: Founded with focus on neuromorphic computing","2023: Appointed Kevin Conley as CEO to lead AI chip development","2024: Secured initial funding of $3.6M","2025: Appointed Eva Lau to Board of Directors","2025: Partnered with academic labs for brain-inspired AI research","2025: TSP1 chip first silicon demonstrated","2026-01: Closed oversubscribed Seed funding round","2026-01: Shipped first TSP1 development kits to Early Access Program"]

Growth metrics

Private company; no public financial metrics available.

Market positioning

Positioned as a specialized neuromorphic computing firm targeting industries requiring low-power, high-performance AI solutions, such as autonomous systems, IoT, and robotics.

Geographic focus

Global, with significant research activity in North America (e.g., Intel, IBM) and Europe (e.g., SpiNNaker projects in Germany/UK).

Patents and IP

Holds patents for super small/efficient AI networks derived from brain circuit research, including full-speech recognition and NLP implementations.

About Kevin Conley

Over 30 years of experience in the semiconductor industry, previously served as CEO & President at Everspin Technologies, Senior VP at SanDisk, VP of Engineering at Corsair. Expertise in AI chip development, storage technologies, and semiconductor product development.

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