Efficient AI inference hardware, customized for your model.

Artificial intelligence is transforming the embedded industry. But deploying AI efficiently using off-the-shelf accelerators is a major challenge.

Custom inference accelerators that are fine tuned for a specific model can deliver exceptional performance. Arguably, designing a dedicated accelerator for every model is expensive, time-consuming, and risky.

What if you can effortlessly customize your AI hardware to optimally match your model requirements?

Our compiler automatically analyzes a neural network and generates an optimized implementation that combines a RISC-V processor with a custom neural-network accelerator.

The compiler intelligently partitions execution between software and hardware, optimizing for the user's priorities whether that's maximum performance, minimum silicon area, or lowest power consumption.

The generated solution can be deployed on both FPGA and ASIC platforms, dramatically reducing development time and accelerating time to market.

The result: multiple fold increase in performance and power efficiency compared with software-only RISC-V implementations.

Stop paying for compute power you don't need. Start building inference solutions that are optimal, efficient, and built exactly for you.