About Navitas Semiconductor Navitas Semiconductor (Nasdaq: NVTS) is a U.S.-based power semiconductor company specializing in gallium nitride (GaN) and silicon carbide (SiC) technologies for high-efficiency energy conversion. Its product portfolio includes GaNFast™ power ICs and GeneSiC™ devices for applications across electric vehicles, fast chargers, data centers, renewable energy, and power tools. Navitas solutions are designed […]
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About SandboxAQ SandboxAQ is a B2B technology company advancing capabilities at the intersection of quantum computing and artificial intelligence. The company develops enterprise solutions that apply quantum-inspired algorithms, advanced encryption, and AI-based simulation to address complex challenges across sectors such as life sciences, financial services, and secure navigation. A key innovation is its Large Quantitative […]
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About Maxwell Labs Maxwell Labs is a Minnesota-based technology startup developing novel photonic cooling solutions to improve thermal management in high-performance computing and AI hardware environments. The company’s platform targets the escalating energy demands and heat generation challenges of next-generation semiconductors, including chips used in AI training, inference, and large-scale data centers. Its research-driven approach […]
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About Pragmatic Semiconductor Pragmatic Semiconductor is an innovator in the design and manufacture of flexible integrated circuits (FlexICs) using thin-film transistor (TFT) technology. Unlike traditional silicon-based chips, FlexICs are ultra-thin, bendable, and can be integrated into non-rigid substrates to support new classes of electronics that are cost-effective, low-power, and scalable. Pragmatic’s circuits are particularly suited […]
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About Blumind Blumind is a deep-tech startup headquartered in Ottawa, Canada, developing an ultra-low-power analog AI platform purpose-built for real-time edge inferencing. The company’s analog compute-in-memory engine integrates machine learning capabilities directly into silicon, enabling inference to be performed locally on sensors and embedded devices with minimal power consumption and latency. This approach significantly reduces […]
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