The integrated package combines Netiotek’s industrial-grade edge computing hardware (NERMPC-265K), ShareGuru’s enterprise semantic document retrieval and Q&A system (ShareQA), and Neuchips AI inference acceleration cards optimized for Transformer architectures.

A Taiwan–Japan tech collaboration led by Neuchips, Netiotek, and ShareGuru will showcase on-premise AI solutions at Japan IT Week, focusing on localized data security and performance for generative AI in corporate environments.

A Neuchips speaker noted ongoing hardware development to accelerate larger model configurations and invited industry leaders to test first-generation solutions to gather feedback for next-generation products.

Executives invite industry leaders to experience the first-generation solutions at the event and offer feedback to inform future product upgrades.

Netiotek provides a robust edge computing foundation designed for long-term on-premise AI operations with strong stability and thermal design.

A disclaimer notes the advertorial nature and PRNewswire origin of the press release.

Exhibitors and attendees are invited to interact with the teams to experience current-generation solutions and provide feedback to shape upcoming generations of on-premise AI hardware and software.

A forward-looking statement from Neuchips emphasizes ongoing development of next-generation hardware optimized for Generative AI to boost on-premise inference speed and accuracy, with industry feedback sought at the event.

ShareGuru contributes its enterprise semantic search and knowledge-management capabilities via ShareQA to enable real-time, high-precision document retrieval.

The trio is positioned as a foundation for localized AI through integrated hardware, software, and knowledge-management capabilities.

ShareGuru’s ShareQA enables real-time, high-precision corporate information retrieval and questions answering, transforming diverse documents into a live knowledge base.

Neuchips highlighted hardware innovation to remove computational bottlenecks and outlined plans for next-generation solutions optimized for larger models, inviting event feedback.