Company: VEEAW
Filing Date: 2025-07-07
Form Type: DRS
Source: 0001213900-25-061586
Chunk: 109

Company: VEEA INC.
Filing Date: 2025-07-07
Form: DRS
Chunk 109
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x platform
infrastructure, together with a captive portal, for multiple ISPs to offer Internet connectivity at most affordable prices along with
free or ad-supported secure voice, data and video communications on local networks. The Ugandan government intends to disseminate announcements
and notifications to its citizens, along with various health and educational content cached at the edge, through the AirLynx networks

AirLynx network solution
is cloud-managed by VeeaCloud with dynamic rules and policy management. It offers flexible billing models beyond typical cellular subscription
services (e.g., time of day, usage, number of devices per subscription, device type) with Bring Your Own Device (BYOD) and subscription
sharing with “friends & family”, where subscription services are consumed across designated devices on one subscription.
Similar to SecureConnect services, Veea realizes revenue from the sale of VeeaHub products, network design professional services and
revenue sharing with service providers.

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3. MetaLynxÔ Service Platform

While early justifications
for edge computing were to address the costs of bandwidth by pre-processing of data at the edge before transmission to the
Cloud, such as in the case of smart cities or building-automation systems, the rise of real-time applications that need fast processing
and response at the edge, such as video processing and analytics, smart grid, artificial intelligence, robotics, and virtual and augmented
reality have greatly expanded the range of use cases for VeeaHub platform. Many times, such applications require uninterrupted operations
(e.g., mission critical applications), significantly lowers latency at most in milliseconds, data security and privacy, which are most
efficiently addressed by a fully integrated edge solution.

For many IoT use cases, without
even considering the application of AI, the edge nodes generate vast amounts of data. Surveillance systems today top data generation
with 20-40 megabytes of data per second but there are use cases where significantly more data is produced at the edge. For these applications
data need to be analyzed at the edge, communicate directly amongst local nodes, and send only filtered data or abstracted data back to
the central cloud. Moreover, IoT applications, supported by Edge AI, are poised to further revolutionize various industry sectors. However,
the consumers of IoT data rely on analytics “on the edge” and in the Cloud to fulfill the tremendous promise of IoT connectivity.
Without analytics, an IoT connection to the network would be like trying to hear a single voice in a