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Intrinsic Semiconductor Technologies

Intrinsic Semiconductor Technologies develops silicon-oxide based resistive random-access memory (RRAM) to provide efficient non-volatile memory directly integrated into advanced processor chips. This technology addresses the memory bottleneck in embedded systems, significantly reducing power consumption and costs while enhancing performance for microcontrollers and edge AI applications.

London, United KingdomFounded 201713500+ followers
Updated 20 months ago

Funding

$10.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Embedded systems face a memory bottleneck due to the limitations of traditional external Flash memory, which consumes significant power and adds to system costs. This bottleneck hinders the performance of microcontrollers and edge AI applications that require fast and efficient memory access.

Solution

Intrinsic Semiconductor Technologies develops silicon-oxide based resistive random-access memory (RRAM) that can be directly integrated into advanced processor chips, eliminating the need for external memory. By integrating the memory directly onto the processor, Intrinsic's RRAM technology significantly reduces power consumption compared to external Flash memory. The direct integration and simple design also contribute to lower manufacturing costs. This approach enables faster data processing and improved performance for microcontrollers and edge AI applications.

Target Audience

The primary target audience includes manufacturers of microcontrollers and edge processors, as well as companies developing edge AI applications.

Features

  • Silicon-oxide based RRAM for non-volatile memory.
  • Direct integration into advanced processor chips.
  • Low power consumption compared to external Flash memory.
  • CMOS compatibility for ease of manufacturing.
  • Simple materials and design for low cost.
  • Enables new compute architectures for edge AI.
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