Company: ARAI
Filing Date: 2025-01-27
Form Type: S-1/A
Source: 0001493152-25-003660
Chunk: 67

Company: Arrive AI Inc.
Filing Date: 2025-01-27
Form: S-1/A
Chunk 67
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 and models to simulate human intelligence and decision-making. We plan to use both technologies distinctly:

a. Machine Learning: Primarily deployed in our AP4 and AP5 Access Points devices for local IoT (Internet of Things) data processing, edge computing (inferencing) for environment and transactional models, and interactions models for drones and robots.

b. Artificial Intelligence: Used more broadly to analyze and derive insights from our network’s transactional and environmental data through complex AI models, but we will also leverage foundational AI models like ChatGPT or LAMA for device based human interactions.

c. More details on our hybrid approach to AI and ML development and the timing of development and foundational data capture necessary for improvements beyond synthetic training are presented in the Business section

3. Operational platform fees. Our network of ALM Access Points, the supporting software and AI plus ML, collectively create an ALM platform that is intended to provide valuable services and insights to all stakeholders in the ALM ecosystem. For example, our automated delivery marketplace (“ADM”) will use a Google-AdSense-like market to help prioritize and optimize high-demand access schedules and space availability for our access point network. The platform will provide a broad array of critical functions for the ALM ecosystem including arrival/departure scheduling, space optimization, smart delivery notifications, micro weather conditions, local restrictions, transactional status updates, and automation issues/obstacles. These capabilities enable ALM automation operators, businesses, and end-customers all to make better value- and data-based operational decisions, such as for a specific Access Point prioritizing time-sensitive food deliveries during peak demand versus optimizing route efficiency for a deferrable delivery at a given time like during the Super Bowl. Another example of ALM platform functionality is our planned mailbox financing exchange (MFE) facilitates dynamic cost-sharing arrangements between financiers, business partners, automation operators, and end-customers. These advanced capabilities will be introduced through our AP5 development and pilot program after development of AP4. At this time we have not engaged any customers or third-parties to participate in, or utilize, these advanced capabilities that have yet to be introduced.

Since inception, we have operated at a loss, with no revenue in 2022 or 2023. Our net losses were $7,321,134 and $2,388,614 for the years ended December 31, 2023, and 2022, respectively. We anticipate continued operating losses as we pursue market penetration in 2024 and first revenues in 2025.

Key