Author | Janson

Editor | Zhi Hao

Car News reported on October 28, that previously, ThunderSoft officially launched AquaDrive AIOS (AquaDrive AIOS) 3.0, further extending AI from in-vehicle voice interaction to task execution, interface generation, and system control.

It is understood that AquaDrive AIOS 3.0 possesses three core capabilities: autonomous generation, autonomous fusion, and autonomous control. It can dynamically generate interaction interfaces based on user intent, integrate functions such as navigation, panoramic view, and automatic parking, and execute travel-related tasks via natural language.

At the press conference venue, ThunderSoft also displayed a demonstration platform modified based on mass-production vehicle models, presenting the application effects of the next-generation AIOS in automobiles.

Besides automotive business, ThunderSoft also launched multiple achievements including TurboX Autonomous Intelligent IoT Platform, Robotics and Embodied AI Solutions, Veda AI Glasses Solutions, and many other results.

At the subsequent media briefing session, ThunderSoft management further responded to industry concerns such as Agent integration in vehicles, OEMs developing AIOS in-house, cockpit-driving integration, whole-vehicle AI control, and automotive business expansion overseas.

This released AquaDrive AIOS 3.0 is a next-generation AI operating system launched by ThunderSoft for smart vehicles, with key upgrades to autonomous generation, autonomous fusion, and autonomous control capabilities.

First is autonomous generation, traditional smart cockpits mainly rely on pre-designed menus and application interfaces for operation, while AquaDrive AIOS 3.0 can dynamically generate corresponding interaction interfaces based on user intent, vehicle status, and real-time scenarios.

For example, after the user states a travel requirement, the system can organize relevant information, call corresponding services, without requiring the user to open different apps one by one.

Second is autonomous fusion, the new system attempts to further connect information related to the cockpit and driving, integrating lane-level navigation, vehicle surrounding environment, 360-degree panoramic view, and automatic parking functions, so that information from different systems can be presented in a more coherent manner.

Third is autonomous control, by introducing agent architecture, AquaDrive AIOS 3.0 can understand natural language commands, perform task planning, and call relevant in-vehicle functions to complete operations.

▲ AquaDrive AIOS 3.0

Compared to traditional voice assistants executing fixed commands, the new system focuses more on the planning, execution, and result feedback of complex tasks.

In the on-site demonstration, ThunderSoft built a demonstration platform based on the Chery Tiggo 8 (Parameters | Images) mass-production vehicle model, demonstrating the technical capabilities of the above applications.

It is worth noting that ThunderSoft's exploration of automotive AI is not limited to smart cockpits.

At the media briefing session, ThunderSoft disclosed that the company has participated in projects of some automakers linking chassis, suspension and other systems with AI, and is exploring the application of AI in areas such as extended-range system energy management and air conditioning energy saving.

Its technical approach is to combine information such as vehicle location, navigation route, road gradient, ambient temperature, and user habits, and optimize the operating status of different vehicle systems with AI assistance.

From a product positioning perspective, ThunderSoft hopes to use the AIOS platform to connect different chips, models, and in-vehicle systems, and co-develop smart automotive products for different brands with automakers.

At the end of the event, ThunderSoft Co-founder & Executive President Geng Zengqiang and Song Yang, General Manager of Smart Auto Product Center of ThunderSoft, accepted group interviews from media including Car News.

Below is the interview transcript, which was excerpted by Car News without changing the original meaning.

▲ Media Briefing Session Site

Q1: Currently, many automakers and tech companies are developing Edge AI and AI operating systems. What differentiated advantages does ThunderSoft have?

Song Yang: Our first advantage is platform neutrality. We can provide full-stack AIOS products and solutions based on customer data, ecosystem, and product concepts.

Cooperation mainly has two models: one is to directly provide Agents, AIOS products, etc. to automakers; the other is to help automakers build their own AIOS platforms.

For example, we established a joint venture with Geely, and also cooperated with other automakers to develop related products.

We hope to gradually transform from a service-oriented company to a product-oriented company, providing complete technical solutions for automakers. The final products may be launched under the automakers' own brands, but the underlying layer uses our technology and solutions.

Q2: After AquaDrive AIOS enters the 3.0 stage, what are ThunderSoft's plans for expanding automotive business overseas?

Song Yang: We laid out overseas very early, especially in automotive business. Currently, the overseas automotive-related team exceeds 1,000 people, covering multiple major automotive markets in Europe and Asia.

In Europe, we acquired two companies engaged in automotive HMI and 3D vision related businesses, accumulating technical capabilities such as automotive interaction, panoramic view, DMS, and OMS.

In markets such as Vietnam, Japan, South Korea, India, and Malaysia, we also have local teams.

A major challenge for automotive AI going overseas is localization. For example, a Southeast Asia project we recently contacted needs to support eight languages, and each language requires native speakers to participate in testing, development, and verification.

Not only language, but living habits, driving habits, and interaction needs of users in different countries are also different, requiring local teams to participate in development.

We believe that Chinese automotive overseas expansion is shifting from pure vehicle sales to a new stage of building local R&D and service capabilities.

Currently, we have also participated in overseas AI projects of multiple Chinese automakers. With Chinese automakers establishing larger R&D teams overseas, the overseas market will become an important development direction for ThunderSoft's automotive business in the next stage.

Q3: Currently, Agent integration in vehicles has not formed a clear application direction. What problems does ThunderSoft believe Agent integration in vehicles actually needs to solve?

Song Yang: Last year, everyone was still discussing what is the most important application of automotive AI, whether it is ordering food, navigation, or other functions.

But this year the direction has changed.

With the development of Master Agent and other technologies, we no longer need to select one most important application. Instead, we hope to connect the original Agents and Apps through a more intelligent system.

In the past, users needed to open different apps to complete navigation, food ordering, etc. operations. Now AI can autonomously plan tasks, call APIs, and generate corresponding interaction interfaces based on user requirements.

In other words, automotive AI is shifting from function calls under fixed scenarios to a system capable of autonomous thinking, orchestration, and task execution.

We believe that an important direction for the next-generation automotive AIOS is to enable AI to not only communicate with users but also truly complete tasks.

Q4: From early AquaClaw related solutions to AquaDrive AIOS 3.0, what changes have occurred in ThunderSoft's automotive agent architecture?

Song Yang: The products we displayed before the Beijing Auto Show were mainly about remotely controlling the car via mobile phone. For example, users say a sentence, and the vehicle can be prepared in advance and the car door opened.

In the second stage, we started to attempt deploying AquaClaw and other agent architectures inside the vehicle system, allowing AI to execute tasks directly.

But during application, we found two problems: one is that models may produce hallucinations, and the other is that response speed is not fast enough.

For example, if the user requests to open a car window, and the command needs multiple processing through the cloud and edge side, it may cause hundreds of milliseconds or even one or two seconds of latency, affecting the experience.

Therefore, in the third stage, we still retain Harness and other agent architectures, but re-split the different service call methods.

For commands like opening a car window that require fast response, it can be completed via more direct service calls without going through a complete complex task planning process.

At the same time, we are also deploying more models and agent capabilities to the edge side to reduce response latency, Token usage costs, and improve system controllability.

▲ ThunderSoft Co-founder & Executive President Geng Zengqiang

Geng Zengqiang: We adopt a model-neutral approach and are not bound to a single model vendor.

For example, the voice model can choose Doubao, and the reasoning model can choose Qwen, DeepSeek, or other solutions according to needs.

The system will also assign tasks based on the vehicle-side computing power situation. If vehicle-side computing power is sufficient, more computation is placed locally; if insufficient, it relies more on the cloud.

The cloud can also choose different models based on task complexity. Simple tasks use lightweight solutions, and complex tasks call stronger models to balance experience and Token costs.

Q5: More and more automakers emphasize full-stack self-research. What customers is ThunderSoft's AIOS mainly targeting? How does it cooperate with automakers?

Geng Zengqiang: Automakers can roughly be divided into two categories.

The first category is new force automakers. They themselves have strong software capabilities and emphasize full-stack self-research, with core technologies usually controlled by themselves. We also cooperate with these enterprises, but primarily participate in some technologies and product development.

The second category is traditional automakers and international automakers.

These enterprises previously relied heavily on suppliers to provide software and hardware. Now they hope to gradually build their own software R&D capabilities, but it is not easy to fully achieve autonomous development in a short period.

Therefore, they usually adopt a walking on two legs approach: on the one hand, building their own R&D teams, and on the other hand, cooperating with technology suppliers to accelerate product development and iteration.

This is also our currently larger customer base.

For example, the joint ventures established with Geely and Volkswagen embody this cooperation model.

Our positioning is not to let all automakers use the same set of ThunderSoft brand AIOS, but to help automakers build their own platforms.

Automakers need to master core parts with differentiated competitiveness, while differentiated basic platform capabilities can be reused more mature solutions, co-developed through product plus service methods.

This year the growth of automotive business was better than our previous expectations, mainly for two reasons.

One is that automotive software is becoming increasingly complex. Suppliers not only need to possess traditional cockpit development capabilities but also AI cockpit development capabilities, and integrate the two.

The second is that automakers' development demand for next-generation AIOS has increased significantly, and everyone wants to apply new technologies to products as soon as possible.

Additionally, new opportunities have emerged in overseas business.

Some international automakers are beginning to reconsider supply chain strategies, expanding the use scope of Chinese supply chains in regions outside the US market to reduce costs and improve development efficiency.

This year we also obtained software and hardware projects from international automakers such as Mazda.

Q6: Currently, AquaDrive AIOS 3.0 mainly showcases cockpit capabilities. In the future, can it further control other systems such as powertrain, chassis, and body?

Song Yang: We are already exploring these directions with automakers.

For example, Chery previously displayed a Daddy Cockpit Concept Demo Vehicle. In addition to controlling functions such as air conditioning and car windows via natural language, it can also make systems such as chassis suspension participate in in-vehicle interaction.

One scenario is that when the vehicle plays a movie, let suspension movement, body posture, and air conditioning vents coordinate with the screen, forming an experience similar to a 4D cinema.

But this also involves an important issue, which is how to ensure safety.

From a technology development perspective, with cockpit-driving integration and computing chip capability improvement, the functions that AIOS can call in the future will increase more and more.

We are currently still discussing extended-range vehicle energy management solutions with one automaker.

For example, for a car adopting a 1.6T extended-range engine equipped with 20 to 30 kWh batteries, how to let the engine always work in a more economical range according to different road conditions?

We hope to introduce information such as navigation route, road gradient, temperature, traffic conditions, and user habits into the AI model to assist in optimizing engine operation strategies and vehicle energy management.

Similar directions also include air conditioning energy saving. We have already developed related AI solutions for automakers, hoping to comprehensively adjust the air conditioning according to environmental conditions inside and outside the car and user needs, rather than relying solely on fixed temperature thresholds.

Additionally, we are also exploring connecting different systems such as air suspension and smart chassis through unified protocols.

Long-term, we hope automobiles can form a unified intelligent computing platform. Under the premise of meeting safety requirements, one intelligent system coordinates more whole-vehicle functions.

With the progress of electrical/electronic architecture and chip technology, AIOS has the opportunity to further evolve from a cockpit operating system to an intelligent system for the whole vehicle.

With the acceleration of large models and agent technologies into vehicles, smart cockpits are evolving from traditional human-machine interaction systems to AI operating systems capable of understanding user intent and autonomously executing tasks.

The release of this AquaDrive AIOS 3.0 reflects ThunderSoft's further layout in the field of automotive AI. From agent interaction to cockpit-driving integration, and then to whole-vehicle energy management, ThunderSoft is attempting to expand AI capabilities to more vehicle systems.

However, whether relevant technologies can truly achieve scaled mass production still needs to address issues such as response speed, system safety, and engineering adaptation. For ThunderSoft, how to transform its own technical accumulation into products that are mass-producible and continuously iteratable by automakers will be the key to the next stage.