SynapseXY builds neuromorphic processors and neural interfaces: event-driven spiking silicon that sips power, and the hardware that lets neurons and machines talk.
What SynapseXY does
Event-driven processors that compute only when signals arrive, like real neurons, for orders-of-magnitude lower power.
On-device intelligence that runs for years on a coin cell, because computation follows the spikes, not a clock.
High-channel-count electrode arrays and low-noise front-ends that read and write neural signals cleanly.
On-chip decoding of neural activity with the latency a closed-loop interface actually requires.
Questions
What is neuromorphic computing?
Hardware modeled on the brain: event-driven spiking neurons instead of clocked arithmetic. It computes only when signals arrive, which makes it extraordinarily power-efficient for sensory and temporal data.
Where does this beat a GPU?
Always-on, low-power edge inference on sparse, event-driven data, audio, vision, and biosignals, where a GPU's constant power draw is impractical.
What are neural interfaces for?
Reading and writing neural signals: restoring movement, sensing, and communication for people with neurological injury, and longer term, richer human-machine interaction.
Is the neural interface work invasive?
We work across the spectrum, from non-invasive arrays to research-grade implantable systems, with safety and ethics governing every stage.
How can we work together?
We partner with research institutions, medical device makers, and edge-AI companies. Reach out and we will find the right fit.
Neuromorphic silicon and neural interfaces, engineered for the real world.
Talk to UsFrom the Blog
A brain runs on roughly twenty watts and outperforms data centers at perception. The lesson is not faster arithmetic; it is a fundamentally different, event-driven way to compute.
Read more →Sensors produce sparse, asynchronous events, a pixel changes, a sound arrives, a nerve fires. Clocked processors throw that structure away. Neuromorphic chips exploit it.
Read more →Reading the brain is less about electrodes and more about extracting a tiny, noisy signal from a hostile environment without harming the tissue you are listening to.
Read more →An interface that only reads the brain is half a system. The moment you want to write back, to restore sensation or close a control loop, latency becomes a hard physiological constraint.
Read more →As intelligence moves onto devices that run for years on tiny batteries, the constant power draw of conventional accelerators becomes the limit. Brain-like computing is the way past it.
Read more →