Company: CCIXW
Filing Date: 2025-12-05
Form Type: S-4/A
Source: 0001193125-25-309933
Chunk: 464

Company: Churchill Capital Corp IX/Cayman
Filing Date: 2025-12-05
Form: S-4/A
Chunk 464
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 with other critical ecosystem participants, including Bosch in the United States and Europe and Tier IV in Japan, to support the development and integration of advanced sensing, compute, and control technologies.

In 2021, we entered into an agreement with Amazon to supply autonomous driving technology.

In 2025, we signed an agreement with a major Japanese trading house that invests in a number of businesses and projects worldwide, pursuant to which the Japanese trading house made an investment in PlusAI. The agreement further contemplates a collaboration between the parties and their affiliates in Japan and other regions of the world and a limited right of first negotiation in favor of the Japanese trading house with respect to PlusAI’s entry into the Japanese market.

These collaborations validate the technical strength and long‑term potential of our platform and reinforce our leadership position within the autonomous driving industry.

Our AI‑Based Virtual Driver Technology

The challenges facing the commercial trucking industry, combined with the scale of the opportunity for autonomy, underscore the importance of having a technology platform that can be deployed safely, reliably, and

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at industrial scale. Our AI‑based virtual driver software has been designed from the ground up to meet these requirements.

AI‑Native Technology Strategy

PlusAI is a pioneer of the Autonomous Vehicle 2.0 (“AV 2.0”) paradigm, which shifts away from traditional robotics‑based architectures toward AI‑native systems powered by large‑scale neural networks. This strategy underpins the design of SuperDrive, enabling more efficient, scalable, and adaptive autonomous driving capabilities.

We develop and train the AI used in the SuperDrive platform internally. These models, including those used for perception, prediction, and planning, are proprietary to us and are trained primarily on data collected by us from testing and developing the platform, supplemented by simulated data generated using tools developed in-house or licensed from third parties.

By leveraging deep learning models trained on vast quantities of real‑world and simulated data, SuperDrive is designed to perform complex driving tasks with humanlike reasoning and to generalize more effectively across unfamiliar scenarios. This data‑driven architecture reduces the software complexity associated with classical rule‑based systems by replacing extensive hand‑coded logic with generalized, model‑driven behavior.

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This foundational design enables:

faster development cycles by reducing manual coding and enabling continuous model improvement;

improved adaptability across diverse environments and edge cases; and

long‑term scalability through architectures that learn rather than require hand‑crafted instructions;

Core AI Model