Company: APXIF
Filing Date: 2025-07-18
Form Type: F-4/A
Source: 0001213900-25-065703
Chunk: 373

Company: APx Acquisition Corp. I
Filing Date: 2025-07-18
Form: F-4/A
Chunk 373
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 used in research, we enforce security protocols including role -basedaccess controls, multi -factorauthentication, data encryption at rest and in transit, and data anonymization and pseudonymization prior to AI training and compliance checks. Health Management & Telemedicine Health management is a key component of Rewell’s value proposition. Rewell initially provided one -on-oneonline sessions with certified nutrigenetic specialists who hold degrees in nutrition and nutrigenomics. In early 2025, we transitioned our Rewell distribution strategy from a direct -to-consumerto a business -to-business-to-consumermodel. As part of this transition, we are currently in the research and development phase of AI Agents designed to support and scale our health management services. These AI Agents are being trained to analyze and synthesize insights from genomic, microbiome, clinical, and lifestyle data, with the goal of providing personalized health guidance to end users. This initiative builds on methodologies and data structures developed during the earlier phases of our operations, which involved direct, one -on-oneinteractions with certified health professionals such as genetic nutritionists. The objective of these sessions is to help users interpret their results and create personalized nutrition and lifestyle plans based on their health goal. These sessions aimed to review the most significant outcomes of the Rewell report, addressing user queries regarding their results, assessing the user’s current routines and habits, proposing improvements, and educating on the impact of these habits on their health. The objective of these sessions was to set small, achievable, long -termgoals to improve or maintain microbiome health and prevent disease development. This educational approach ensures the report’s findings are used actively by rather than solely being read and stored away. 184 We expect that the first commercial use of our AI Agents may begin as early as 2026, subject to continued progress in foundational large language models (LLMs), regulatory developments, and successful internal testing and validation. We acknowledge that AI technologies are rapidly evolving, and our timelines are subject to acceleration or delay based on technological and regulatory developments. Our AI Agents will be built on third -partyinfrastructure, including LLMs and other machine learning technologies developed by external vendors. While these models provide significant potential to increase the scalability and efficiency of personalized healthcare, they also introduce critical risks, including bias, errors in medical interpretation, and the risk of overreliance by us and the end consumers of our products on automated outputs. All outputs generated by AI Agents will remain subject to human oversight, especially where medical recommendations are involved. Licensed