VEEA and VAPOR IO Announce a Strategic Partnership to Provide Turnkey AI-as-a-Service Pioneering Solutions for AI Inferencing, Federated Learning, Agentic AI and AIoT

For enterprise applications, such as Smart Manufacturing, Smart Warehouses, Smart Hospitals, Smart Schools, Smart Construction, Smart Infrastructure, and many others, Veea Edge Platform collects and processes the raw data at the Device Edge, where user devices, sensors and machines connect to the network, most importantly, for reasons of low-latency, data privacy and data sovereignty. VeeaWare full stack software running on VeeaHub devices and on third-party hardware solutions with GPUs, TPUs or NPUs, such as NVIDIA AGX Orin and Qualcomm Edge AI Box-based hardware on a Veea computing mesh, provide for the full gamut of AI inferencing with cloud-native edge applications and AI-driven cybersecurity with bespoked Agentic AI and AIoT for the specific use cases. Combined with its VeeaCloud management functions, AIoT platform and extension of network slicing through the LAN with SDN and NFV, Veea Edge Platform offers an unrivaled capability for AI inferencing for enterprise use cases at the edge.

The core of Vapor IO’s Zero Gap AI is built around Supermicro MGX servers with the NVIDIA GH200 Grace Hopper Superchip for high-performance accelerated computing and AI applications. The Zero Gap AI makes it possible to simultaneously deliver AI inferencing and train complex models while supporting 5G private networks, including NVIDIA Aerial-based 5G private network services. Through a PoC together with Supermicro and NVIDIA in Las Vegas, Vapor IO demonstrated how Zero Gap AI customers can receive the benefits of AI inferencing for a range of use cases including by those in mobile environments with the highest level of performance and reliability that may be achieved today. For low-latency use cases, Zero Gap AI is offered as high-performance micro data centers, strategically placed in close proximity where AI inferencing is delivered. Zero Gap AI offering provides for the AI tools, libraries, SDKs, pre-trained models, frameworks and other components that may optionally be employed to develop AI apps.