Company: ARAI
Filing Date: 2025-05-13
Form Type: S-1/A
Source: 0001641172-25-009841
Chunk: 75

Company: Arrive AI Inc.
Filing Date: 2025-05-13
Form: S-1/A
Chunk 75
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 obstacles. The ALM Platform is not currently in use, as it remains in the developmental stage     
 and is aspirational in nature. There is no assurance that we will successfully develop or         
 implement these tools, or that the ALM Platform will achieve the intended functionality or        
 market acceptance.                                                                                |
| 3. | AI                                                                                                
 and ML technology leveraging two distinct applications of artificial intelligence and machine     
 learning: (1) edge-based inferencing models running directly on Access Points for real-time       
 operations, and (2) centralized AI systems analyzing network-wide data to generate business       
 insights and ecosystem improvements. We have already demonstrated initial AP4 AI capabilities     
 to customers, with comprehensive implementation planned for 2025 delivery. We plan to             
 develop further advanced AI capabilities for AP5 in 2025 and 2026. The                            
 effectiveness and value of our AI/ML models are directly correlated with delivery                 
 network utilization and the associated transactional data volume. Beginning in 2025,              
 we expect to accumulate 12-18 months of operational and delivery data, reaching the               
 critical mass necessary to begin improving the value of our proprietary ALM models                
 and insights. This unique and growing dataset will encompass transactional patterns,              
 operational performance metrics, and environmental conditions across our network, creating        
 a valuable proprietary asset for improving autonomous last-mile delivery operations.              
 Note that to meet our data accumulation goals and maximize the effectiveness of our proprietary   
 ALM models, we believe a minimum of 200 deployed and actively utilized ALM Access Points,         
 with an average daily volume of 3 deliveries, will be necessary to generate sufficient data       
 over 18 months of operations. If fewer units are deployed or the average utilization rate         
 per unit falls below 50%, the rate of data accumulation will slow, delaying both the expected     
 timeframe for likely AI improvements and the monetization of the resulting insights. These        
 metrics—deployment scale and utilization rate—are critical to achieving the desired               
 scale for AI/ML and network-wide operational improvements.                                        |

Management believes that
Arrive is pioneering the emerging market for the automated exchange of packages and goods between people, robots, and drones with our
autonomous last mile (“ALM”) mailbox but there are no guarantees that we are right or will be successful in our efforts.
We are advancing our technology through structured customer and partner trials or pilots for which the Company receives no revenues.
All pilots operate under executed Statements of Work (SOW). Active customer agreements and SOWs differ in that SOWs