VEEA INC.VEEA

Veea platform uses local computing to support agentic AI applications for health data.

“The platform, built on VeeaONE, connects health records, wearable and sensor data, and biological measurements into a patient-controlled longitudinal health profile. Local computing supports agentic AI applications close to the patient, with patient-directed permissions governing access to personal data. Rollout begins with connected health services and will expand to clinician-supervised diagnostics and therapy pathways as clinical validation and applicable regulatory authorizations permit.”

VeeaONE platform enables machine learning with AI training, inferencing and agentic AI at the edge.

“The Company is dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that (a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, (b) spawns hyperconvergence of computing, multiaccess communications and storage, (c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), and (d) enables machine learning with AI training, inferencing, and agentic AI at the edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack. Our end-to-end edge-cloud platform is referred to as VeeaONETM (“VeeaONE”) platform.”

Advanced intelligence accelerated by frontier AI models for edge use cases.

“Veea was formed based on management’s strong belief that true intelligence applicable to the edge use cases emerges from networks with real-world data and compute, and not the other way around. Everything in nature, including the formation of human societies, demonstrates that intelligence does not reside in a single node. It emerges when distributed “agents” (i.e., humans, elephants, zebras, ants, bees, mycelium, bacteria and viruses) exchange information, adapt, and coordinate toward shared outcomes. It is now becoming amply clear that advanced intelligence, accelerated by “manufactured” frontier AI models, is rapidly becoming abundant and widely available on an open-source basis, especially as they apply to the edge use cases supported by the Company. This has been evidenced recently by models such as (i) the open-source model released by NVIDIA, Nemotron 3 Ultra, a 550-billion-parameter open-weight frontier model optimized for advanced planning, code execution, and long-running AI agents providing for expert models and delivering high-speed inference, with up to a one million token context window, and (ii) the Kimi K3 open-source AI model, which matches the benchmark scores of Anthropic’s most advanced frontier model.”

Veea discusses its edge platform enabling agentic AI and cites Mercedes-Benz using a Liquid AI model as an example.

“For AI models, especially for Physical AI at the edge, context is everything. With cameras, sensors and networked computing at the edge, VeeaONE can continuously deliver the ever-changing context for most use cases, which provides for fine-tuning of the models. Veea management believes that its leading end-to-end edge platform will facilitate the transition of AI creation from specialized teams to ordinary individuals and businesses with just simple prompts and Agentic AI. VeeaONE network capabilities support the migration of frontier-level capabilities from AI factories onto edge devices (e.g., gateways, hubs, servers, etc.), vehicles, robots, and others with Agentic AI Mixture of Experts (MoEs) at the edge. This will enable Edge AI models to become personalized for individuals and businesses with recursive self-improvement, ultimately, offering recommendations and predictions that can influence, or effectively make, economic, corporate, medical, and personal decisions. As an example of this type of Agentic AI adaptation at the edge, Mercedes-Benz has incorporated a Liquid AI agentic model that is only 600 MB in size and that, without relying on cloud services at all times, highly personalizes the car’s environment for its driver and passengers with recursive self-improvement.”

Veea claims it is one of the first to market with patented tech enabling agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform software stack.”

VEEA INC. enables machine learning with AI training, inferencing, and agentic AI at the edge via its VeeaONE platform.

“The Company is dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that (a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, (b) spawns hyperconvergence of computing, multiaccess communications and storage, (c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), and (d) enables machine learning with AI training, inferencing, and agentic AI at the edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack. Our end-to-end edge-cloud platform is referred to as VeeaONETM (“VeeaONE”) platform.”

VEEA INC. enables machine learning with AI training, inferencing, and agentic AI at the edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are onf of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform software stack.”

Veea enables machine learning, inferencing and Agentic AI at the Edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence (“ AI ”) to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE TM (“ VeeaONE ”) platform.”

Veea enables machine learning, inferencing and Agentic AI at the Edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE Ô (“ VeeaONE ”) platform.”

Veea differentiates its Edge AI infrastructure from foundational model developers such as OpenAI creating Agentic AI.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company, such as Veea with VeeaONE platform, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In many cases, these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed, typically holding the top spot for just a few weeks before newer, open-source variants emerge.”

Veea offers multimodal AI agents as part of its recurring revenue services for SMB customers.

“SecureConnect Ô turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge Ô , inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea discusses application of edge AI models with multimodal Agentic AI and SLMs.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“SLMs”),”

Veea has developed and brought to market edge platform enabling Agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô . Our end-to-end edge-cloud platform is referred to as VeeaONE Ô platform.”

VeeaONE platform enables machine learning, inferencing, and Agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE™ platform’s software stack VeeaWare™ (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE™ (“ VeeaONE ”) platform.”

Differentiates Veea infrastructure from foundational AI model developers like OpenAI.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company, such as Veea with VeeaONE platform providing for Physical AI and inferencing, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In some cases, certain versions of these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed.”

SecureConnect offers AI-driven cybersecurity, inferencing, and multimodal AI agents.

“SecureConnect™ turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge™, inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea supports Edge AI models with inferencing and multimodal Agentic AI.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“ SLMs ”),”

VeeaONE platform enables AI training, inferencing, and agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform ☐ software stack.”

VeeaONE platform enables AI training, inferencing, and agentic AI at the edge.

“The Company is dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that (a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, (b) spawns hyperconvergence of computing, multiaccess communications and storage, (c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), and (d) enables machine learning with AI training, inferencing, and agentic AI at the edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack. Our end-to-end edge-cloud platform is referred to as VeeaONETM (“VeeaONE”) platform.”

Veea describes its VeeaONE platform enabling Edge AI including Agentic AI.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence (“ AI ”) to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE TM (“ VeeaONE ”) platform.”

Veea describes its VeeaONE platform enabling Edge AI including Agentic AI.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE Ô (“ VeeaONE ”) platform.”

Veea differentiates its Edge AI infrastructure from foundational AI model developers like OpenAI.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company, such as Veea with VeeaONE platform, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In many cases, these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed, typically holding the top spot for just a few weeks before newer, open-source variants emerge.”

Veea offers AI-driven cybersecurity, inferencing, and multimodal AI agents via SecureConnect for recurring revenue.

“SecureConnect Ô turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge Ô , inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea discusses application of Edge AI models with federated learning, inferencing, and multimodal Agentic AI.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“SLMs”),”

Veea describes its VeeaONE platform enabling Edge AI including agentic AI.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform ☐ software stack.”

Platform enables machine learning with AI training, inferencing, and agentic AI at the edge.

“The Company is dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that (a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, (b) spawns hyperconvergence of computing, multiaccess communications and storage, (c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), and (d) enables machine learning with AI training, inferencing, and agentic AI at the edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack. Our end-to-end edge-cloud platform is referred to as VeeaONETM (“VeeaONE”) platform.”

VEEA describes its patented technologies enabling agentic AI at the device edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the Veea Edge Platform Ô software stack.”

VEEA enables machine learning, AI training, inferencing and agentic AI at the edge on its VeeaONE platform.

“The Company is dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that (a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, (b) spawns hyperconvergence of computing, multiaccess communications and storage, (c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), and (d) enables machine learning with AI training, inferencing, and agentic AI at the edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack. Our end-to-end edge-cloud platform is referred to as VeeaONETM (“VeeaONE”) platform.”

VEEA enables machine learning, AI training, inferencing and agentic AI at the edge on its Veea Edge Platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the Veea Edge Platform Ô software stack.”

VEEA enables machine learning, inferencing, and Agentic AI at the Edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence (“ AI ”) to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE TM (“ VeeaONE ”) platform.”

VEEA enables machine learning, inferencing, and Agentic AI at the Edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected , while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE Ô (“ VeeaONE ”) platform.”

Veea differentiates its Edge AI infrastructure from foundational AI model developers like OpenAI.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company , such as Veea with VeeaONE platform, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In many cases, these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed, typically holding the top spot for just a few weeks before newer, open-source variants emerge.”

Veea offers multimodal AI agents as a subscribed service generating recurring revenue.

“SecureConnect Ô turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge Ô , inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea describes application of Edge AI models with federated learning and agentic AI.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“SLMs”),”

Veea enables machine learning with AI training, inferencing and agentic AI at the Edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform ☐ software stack.”

Veea enables machine learning with AI training, inferencing, and Agentic AI at the Edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence (“ AI ”) to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE TM (“ VeeaONE ”) platform.”

Veea enables machine learning with AI training, inferencing, and Agentic AI at the Edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected , while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE Ô (“ VeeaONE ”) platform.”

Veea differentiates from foundational AI model developers such as OpenAI.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company , such as Veea with VeeaONE platform, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In many cases, these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed, typically holding the top spot for just a few weeks before newer, open-source variants emerge.”

Veea offers AI-driven cybersecurity services and multimodal AI agents to customers.

“SecureConnect Ô turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge Ô , inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea applies Edge AI models with inferencing and multimodal Agentic AI.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“SLMs”),”

Veea claims to be first to market with patented tech enabling agentic AI at the device edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform ☐ software stack.”

VEEA enables machine learning, AI training, inferencing and Agentic AI at the Edge with its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and artificial intelligence (“ AI ”) to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE platform’s software stack (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE TM (“ VeeaONE ”) platform.”

Veea claims to be first to market with patented tech enabling agentic AI at the device edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected , while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are one of the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “ Edge ”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“ Edge Computing ”) c) provides for Cloud-managed applications at the Edge (“ Hybrid Edge-Cloud Computing ”), and d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“ Edge AI ”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the VeeaONE Ô platform’s software stack VeeaWare Ô (“ VeeaWare ”). Our end-to-end edge-cloud platform is referred to as VeeaONE Ô (“ VeeaONE ”) platform.”

Veea differentiates its edge AI infrastructure from foundational model developers such as OpenAI and Edge Impulse.

“It is important to differentiate between an investment into an Edge AI-enabling infrastructure company , such as Veea with VeeaONE platform, vs. a foundational AI model development company or other model developers (e.g., OpenAI or Edge Impulse), developing Large Language Models (“ LLMs ”), Small Language Models (“ SLMs ”), Agentic AI, federated machine learning, etc. In many cases, these models are freely made available on an introductory basis or longer-term in order to rapidly penetrate into a vast potential market. However, as headlined on a daily basis, AI models evolve at breakneck speed, typically holding the top spot for just a few weeks before newer, open-source variants emerge.”

Veea offers multimodal AI agents for IoT, inferencing, inventory, and advertising as subscribed services generating recurring revenue.

“SecureConnect Ô turns complex IT for delivery of broadband services, with cybersecurity, over a LAN with microsegmentation of traffic and device type profiles, that is PCI compliant for POS and payment terminals, into a plug-and-play solution with value-added services tailored for Small to Medium-size Businesses/Enterprises (SMBs/SMEs) customers. Our business model for SecureConnect provides for a monthly recurring revenue from cloud management, AI-driven cybersecurity services, and to the extent subscribed to by the end-users, IoT gateway services, AI inferencing (e.g., CCTVs with computer vision application at retail locations and construction sites) and multimodal AI agents (e.g., context-aware insights fused together with network insights such as for location-based targeted advertising based on Veea’s AdEdge Ô , inventory management, and other applications) to Veea as a share of the revenue collected by the service provider.”

Veea applies edge AI models with federated learning, inferencing, multimodal agentic AI and SLMs.

“Application of Edge AI models supported by federated machine learning with any combination of inferencing and multimodal Agentic AI, optionally, with Small Language Models (“SLMs”),”

Veea claims to be first to market with patented tech enabling agentic AI at the device edge via its VeeaONE platform.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the VeeaONE platform ☐ software stack.”

Veea offers edge AI including inferencing, federated learning and agentic AI to SMBs.

“Examples of SMB use cases addressed by Edge AI that increase MNO’s ARPU • Broadband SD - WAN services with AI - driven cybersecurity • CCTV cameras with computer vision and inferencing for surveillance, fire and gas detection, loss prevention, etc. • Honeywell Niagara - based air quality, lighting, HVAC, and energy management • IoT use cases such as smart lock, leak detectors, asset tracking • Location - based contextual edge advertising • Content management (NVMe - based CDN / NAS with data parsing and blockchain) Through Partnerships with network operators, Veea is poised for strong growth % of Workforce Employed % of All Businesses Number of SMEs/SMBs Country/ Region ~46% 99.9% 34.8 million United States ~62% 99.8% 1.2 million Canada ~72% 99.8% 4.1 million Mexico ~67% 99% 10 million Latin America & Caribbean Initially Targeting SMBs and SMEs in Americas Platform - as - a - Service (PaaS) • Product sales • Monthly Recurring Revenue (MRR) from Revenue Sharing - Cloud - management of VeeaHub and third - party devices - Cybersecurity Services - Value - added services • Edge AI (e.g., inferencing, federated learning, Agentic AI) Markets for SecureConnect solution with value - added services is not demand constrained with strong pent - up demand SecureConnect Typical Set - up Business Overview I N T E L L I G E N T L Y C O N N E C T E D 9”

Veea MetaLynx platform offers multimodal digital twins with agentic AI for edge solutions.

“Create, deploy and scale AI - rich Smart Solutions and IoT applications ▪ MetaLynx Platform delivers “ Total Fabric ” for end - to - end VeeaCloud - managed edge deployments for AI - powered Smart Solutions. ▪ Creates a heterogenous mesh network of VeeaHub products and select third - party devices, running VeeaWare software stack middleware, with any combination of CPUs, GPUs, TPUs, DPUs and/or NPUs - embodies: • SecureConnect for edge computing with IoT gateway and advanced cybersecurity, which is a must have for “Edge AI”, • AirLynx network slicing capabilities for priority of service, latency and bandwidth management with peer - to - peer encrypted tunneled connections over LAN/WAN, ▪ Cloud - managed VeeaHub IoT Gateway incorporates a unique implementation of LoRaWAN gateway and supports most wired and wireless IoT protocols. ▪ By integrating multimodal data with contextual awareness, the platform enables real - time processing, rapid adaptation, energy efficiency, and enhanced decision - making capabilities. • Offers multimodal Digital Twins with Agentic AI. • Example of MetaLynx solution for Smart Construction: https://youtu.be/6QpRkqDoNdw ▪ Provides tokenization of physical assets and infrastructure, e.g., Real World Assets (RWAs), enhancing transparency and trust while providing robust edge analytics. Total Fabric Provides real - time decision - making, scalability, and enhanced performance for complex AI - driven edge applications. Portable Deployment Near premises GP”

Veea developer portal includes AI toolkit for applications with machine learning and agentic AI.

“Platform Ecosystem Groundbreaking Hybrid Edge - Cloud Computing Ecosystem ▪ An end - to - end cloud - managed platform to provide for edge applications with Edge AI and cybersecurity on a turnkey basis. ▪ Hyperconverged* Edge Computing with storage on a networking and computing mesh of heterogenous devices. • Linux server with Dockerized containers • Multiaccess with Wi - Fi Access Point (AP) and IoT Gateway (Bluetooth Classic/BLE, Matter, Thread, Zigbee, optional LoRaWAN® Gateway) • Wired and/or wireless broadband including 5G FWA • Router with SD - WAN and advanced networking • Firewall with enterprise - grade cybersecurity protection • NVMe - based AI - powered CDN and distributed network storage ▪ Designed for indoor, outdoor, and harsh environments ▪ VeeaCloud for management and Kubernetes® orchestration of devices and applications reducing operational complexities. ▪ Veea Developer Portal, with IoT and AI toolkit for custom applications with machine learning, inferencing and Agentic AI . * Hyperconverged refers to the convergence of computing, storage, networking, and virtualization functions within a single system or platform. I N T E L L I G E N T L Y C O N N E C T E D 16”

VEEA is first to market with patented technologies enabling agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the Veea Edge Platform Ô software stack.”

VEEA enables machine learning with AI training, inferencing, and agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected , while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network (the “Edge”), b) spawns hyperconvergence of computing, multiaccess communications and storage, (“Edge Computing”) c) provides for Cloud-managed applications at the Edge (“Hybrid Edge-Cloud Computing”), d) enables machine learning with AI training, inferencing, and Agentic AI at the Edge (“Edge AI”) including AI-driven cybersecurity for heterogenous networks. Such networks have given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run on the Veea Edge Platform’s software stack (“VeeaWare”).”

VEEA Nexus is the central agentic AI orchestration engine for automated actions.

“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 or without GPUs or DPUs included in the mesh network, provide sufficient resources for training of submodels. Moreover, Veea Nexus is the central agentic AI orchestration engine that transforms real-time analytics and insights into automated actions. By providing a unified, centralized automation engine, Nexus eliminates the need for each individual app to build its own automation logic. Instead, any app can integrate seamlessly with Nexus (i.e., becoming "Nexus-enabled"), allowing rapid deployment of sophisticated agentic workflows.”

VEEA enables machine learning with AI training, inferencing, and agentic AI at the edge.

“We are dedicated to simplifying the journey towards creating a world in which virtually everyone and everything is intelligently connected, while bringing applications and AI to the edge of the network. Most service providers, equipment suppliers, system integrators and even hyperscalers have adopted or advocated for similar solutions to various degrees either independently or in collaboration with the Company. However, to our knowledge, we are the first to market with patented technologies that a) bring virtualized data center capabilities to the far edge of the network, commonly referred to as the Device Edge, where all wired and wireless devices connect to the network, b) spawns hyperconvergence of computing, multiaccess communications and storage, c) provides for Cloud-managed applications at the Edge, d) enables machine learning with AI training, inferencing, and agentic AI at the Edge including AI-driven cybersecurity for heterogenous networks. Such networks are given rise through any combination of our developed devices and third-party devices, with CPUs, GPUs, TPUs, DPUs and/or NPUs, that run the Veea Edge Platform Ô software stack.”