Company: VEEAW
Filing Date: 2025-08-12
Form Type: S-1/A
Source: 0001213900-25-074676
Chunk: 93

Company: VEEA INC.
Filing Date: 2025-08-12
Form: S-1/A
Chunk 93
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 latency for real-time decisions at the edge vs. round-trip cloud delay, |

| ● | Lower                 
 data transport costs, |

| ● | Data                     
 privacy and sovereignty, |

| ● | Reliability                                                                    
 including “always-on” availability for mission critical applications and fault 
 tolerance if required,                                                         |

| ● | Scalability,                                                                        
 especially, with heterogenous networks supported by Veea’s full-stack edge-to-cloud 
 software platform,                                                                  |

| ● | Contextual                                 
 awareness of connected device at the edge, |

| ● | Improves                                                                                  
 resilience in intermittent connectivity scenarios, addressing connectivity and networking 
 challenges with data traffic micro-segmentation and network profiles at the edge,         |

| ● | Supports                                                   
 compliance with regional data sovereignty regulations, and |

| ● | Significant                            
 cost savings compared to alternatives. |

Edge AI, the ability to run intelligent algorithms locally, literally on machines or devices, or in short proximity of where data is generated, giving rise to how we live, work, and move, while helping to create new industries, redefining mobility, revolutionizing healthcare, transforming energy systems, and enabling more human-centered experiences. By moving AI from centralized clouds to the very edge of networks, Edge AI enables a new generation of autonomous machines and experiences that were once confined to science fiction. We believe that the societal impact will be profound. Edge AI market size in 2024 was on the order of US$20.8 billion, and is expected to reach US$24.9 billion in 2025, and US$66.5 billion by 2030, with a 21.7% CAGR (2025–2030). 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. 50 In contrast, once HCI is deployed, spanning compute, storage, LAN/WAN networking, including 5G, and