Euclyd
Euclyd provides AI inference hardware that delivers roughly 100× higher power efficiency and lower cost per token than leading solutions, enabling faster, cheaper, and more sustainable compute. By designing chips from the logic‑gate level, the company reduces footprint and makes advanced AI models accessible in a wider range of locations. Its European‑engineered, environmentally conscious approach targets scalable, responsible AI deployment for diverse customers.
- Artificial Intelligence
- Hardware
- Semiconductor
Funding
Founders
Founder details are not available yet.
Product
Problem
Running AI inference workloads on conventional hardware consumes large amounts of power and incurs high cost per token, limiting the scalability and sustainability of machine‑learning applications, especially in edge or resource‑constrained environments.
Solution
Euclyd designs AI inference chips from the logic‑gate level to achieve roughly 100× higher power efficiency and lower cost per token than leading solutions. The hardware delivers fast token processing while dramatically reducing energy use and physical footprint, enabling more affordable and environmentally responsible AI deployment. By providing this efficiency‑first compute, Euclyd allows enterprises and developers to run advanced models at scale in a broader range of locations, from data centers to edge devices. The platform integrates with standard AI frameworks, delivering seamless acceleration without extensive software rewrites.
Target Audience
Primary customers are enterprises, cloud providers, and developers who require high‑performance, cost‑effective AI inference for data‑center, edge, or embedded applications.
Features
- Custom logic‑gate‑up architecture optimized for inference, delivering up to 100× higher power efficiency
- Low cost per token processing, reducing operational expenses for high‑throughput workloads
- Compact chip design that minimizes hardware footprint for edge and on‑premise deployments
- Compatibility with popular AI frameworks and model formats for easy integration
- High token‑per‑second throughput supporting real‑time inference demands
- Built‑in support for sustainable operation, lowering overall energy consumption of AI workloads