Core contributor across SYNCH, TEMPO, MeM-Scales, and ANDANTE — all focused on brain-inspired hardware architectures and spiking neural network processors.
SYNSENSE AG
Swiss SME designing ultra-low-power neuromorphic processors and spiking neural network chips for edge AI and wearable applications.
Their core work
SynSense AG is a Zurich-based SME specializing in neuromorphic computing hardware — processors that mimic how biological neurons work, enabling ultra-low-power AI inference at the edge. They design spiking neural network chips (ASICs) for applications like wearable medical devices and real-time signal processing. Their work bridges neuroscience-inspired architectures with practical semiconductor design, turning brain-like computing concepts into deployable silicon products.
What they specialise in
TEMPO, MeM-Scales, and ANDANTE all involve deploying neural network models on specialized low-power hardware, including ASICs and analog spiking microprocessors.
TEMPO and MeM-Scales explored MRAM, OxRAM, phase change memory, and electrochemical metallization memories for neuromorphic architectures.
SYNCH project developed a brain-silicon neural closed-loop hybrid system integrating BCI with memristor-based hardware.
DynapIP (which they coordinated) targeted wearable medical signal processing, and ANDANTE focused on AI at the edge — indicating a push toward commercial deployment.
How they've shifted over time
SynSense's early H2020 work (2019) centered on foundational neuromorphic concepts — memristors, brain-computer interfaces, neural plasticity, and general-purpose spiking chip design (SYNCH, TEMPO). By 2020, their focus shifted toward specific memory technologies for neuromorphic architectures (MeM-Scales) and practical edge AI deployment (ANDANTE), signaling a move from research exploration to application-ready hardware. The trajectory shows a company maturing from neuroscience-inspired R&D toward commercially viable, ultra-low-power AI processing products.
SynSense is moving from neuromorphic research toward deployable edge AI hardware, making them increasingly relevant for partners needing ultra-low-power inference in real-world products.
How they like to work
SynSense primarily operates as a specialist partner (4 of 5 projects as participant), contributing neuromorphic hardware expertise to larger consortia. With 47 unique partners across 11 countries, they maintain a broad European network rather than a tight circle of repeat collaborators. Their one coordinated project (DynapIP) was an SME instrument phase 1 — a solo feasibility study — suggesting they prefer contributing deep technical capability to multi-partner research projects rather than leading large consortia.
SynSense has collaborated with 47 distinct partners across 11 countries, building a wide European network concentrated in the neuromorphic computing and advanced semiconductor research community. Their Swiss base connects them to strong academic and industry ecosystems across the EU.
What sets them apart
SynSense occupies a rare niche as an SME that actually designs and fabricates neuromorphic processors — most companies in this space are either large semiconductor firms or university spin-offs without commercial products. Their combination of neuroscience understanding (BCI, neural plasticity) and semiconductor engineering (ASIC design, memory integration) makes them a bridge between academic brain research and industrial AI hardware. For consortium builders, they bring something hard to find: a small, focused team that can deliver physical neuromorphic chips, not just algorithms or simulations.
Highlights from their portfolio
- SYNCHLargest funding (EUR 609K) and most ambitious scope — building a closed-loop brain-silicon hybrid system combining BCI, memristors, and neural networks.
- ANDANTEMost commercially oriented project (EUR 319K) focused on bringing AI to edge devices, representing SynSense's push toward market-ready technology.
- DynapIPTheir only coordinated project — an SME Instrument feasibility study for ultra-low-power neuromorphic wearable medical devices, revealing their core commercial ambition.