WiCi provides a wireless compute layer that lets personal devices access high‑performance GPU resources without added hardware. By combining a purpose‑built Wi‑Fi chip, a unified protocol, and an SDK, WiCi enables real‑time, private AI workloads on laptops, tablets, and phones as if the remote GPU were local, delivering low‑latency, high‑bandwidth performance.
Funding
Funding not disclosed
Founders
Product
Problem
Mobile and edge devices such as laptops, tablets, phones, and robots lack sufficient on‑board GPU power to run modern AI models in real time, and adding dedicated accelerators increases size, weight, and thermal load. This limits the ability to deliver private, low‑latency AI experiences directly on the device.
Solution
WiCi creates a wireless compute layer that lets existing devices access a remote GPU over standard Wi‑Fi as if it were locally attached. The WiCi Protocol provides a unified stack—including driver, SDK, and wireless computation optimizations—that abstracts the remote GPU and presents it to applications as a local resource. A purpose‑built Wi‑Fi silicon chip handles low‑latency, high‑bandwidth GPU traffic, ensuring real‑time performance without the need for additional hardware on the client device. The overall WiCi Computing Architecture integrates the wireless chip with memory and storage to deliver a single, cohesive system for off‑device AI compute. This approach enables private AI inference and training on personal devices while keeping the form factor, weight, and heat generation unchanged.
Target Audience
Primary customers are developers and manufacturers of laptops, tablets, smartphones, and robotic or IoT devices that require on‑device AI capabilities without adding bulk, weight, or thermal constraints.
Features
- WiCi Protocol stack that abstracts remote GPU access, allowing any application to treat the GPU as local
- Dedicated Wi‑Fi silicon chip optimized for low‑latency, high‑throughput GPU data transfer over standard Wi‑Fi
- Unified computing architecture that combines the wireless chip with memory and storage for seamless operation
- SDK and driver support for easy integration into existing software ecosystems on laptops, tablets, phones, and robots
- Real‑time, private AI inference without reliance on cloud services, preserving data locality and security