Company: VEEAW
Filing Date: 2025-04-15
Form Type: 10-K
Source: 0001213900-25-032215
Chunk: 6

Company: VEEA INC.
Filing Date: 2025-04-15
Form: 10-K
Item: Item 1
Chunk 6
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 Niagara that is integrated with the Niagara Framework®  (developed by Tridium,
Inc., a wholly owned subsidiary of Honeywell International, Inc.), the leading platform for connecting to and managing building systems.
Veea Edge can deliver actionable insight to building managers and homeowners regarding data generated by HVAC, lighting, access control,
fire safety, plumbing and surveillance systems. Building managers and homeowners can use this data to reduce electricity usage and carbon
emissions through continuous monitoring and optimization, building management automation, and analysis of usage patterns and environmental
conditions. Veea enhances the traditional Niagara Framework by capturing and pre-processing operational data locally, before augmenting
it with cloud processing, along with interconnecting wired and wireless sensors. Given the dynamic nature of building configurations,
designs, and materials, flexibility in deploying wireless sensors, connection to the Internet, and local data processing is required.

Converged Private Wireless Networks and Edge AI

Wi-Fi
and private 4G/5G networks are converging to provide wider coverage, faster speeds, and connectivity across a broad range of devices
and sensors. By integrating the two technologies, devices can connect seamlessly to the best available network coverage from Veea Edge
Platform and private 4G/5G network. A converged network takes advantage of Wi-Fi’s ability to handle large amounts of data traffic,
at lower network expense in areas densely populated by people and machines, with 5G’s reliability and low latency over large distances.

Veea’s
hyper-converged edge platform uniquely complements this new technology through its vTBA 5G interworking functionality allowing 5G and
non-5G endpoints to be managed from a converged controller. This is unique to the industry and overcomes the need to replace many fully
functioning Wi-Fi or IoT endpoints, especially for industrial and enterprise use cases, and allows legacy wired and wireless endpoints
to remain connected via the Veea Edge Platform.

Federated learning allows large scale datasets to be used for training
models while keeping the data private in each VeeaHub node, within a cluster of VeeaHub products at the edge or on a wide area private
network with VeeaHub units in vTBA-based Trust Domains. For many use cases of Edge AI delivered through Veea Edge Platform, such as Smart
Retail, Smart Building and Energy Management, Smart Farming, and others, current models of VeeaHub product supporting up to 8 GB of RAM
and up to 2 TB of memory, with