How Greater China Organizations Power AI And Compliance At Scale

Organizations across Greater China are heavily investing in data-driven technologies to deliver innovative digital services and experiences. According to Morgan Stanley Research, AI investments in China alone could deliver a 52% return on invested capital by 2030*.

However, not every company is equipped to handle the challenges that arise from managing and using data at scale. Managing an exponentially growing number of datasets introduces infrastructure complexity, compounded by rising data security and compliance pressures.

Legacy data infrastructures built on traditional Relational Database Management Systems (RDBMS) have become a significant hindrance—particularly when trying to build and scale the next generation of AI applications.

For many organizations, the key to success lies in modernizing their data architectures, and adopting a more flexible database model. This is what three leading companies across Greater China are doing with MongoDB.

Votee AI: Powering the world’s first Cantonese LLM

Votee AI specializes in building and delivering tailored, AI-driven solutions for industries ranging from banking and hospitality to retail and telecommunications. Votee AI’s agentic AI platform caters to the linguistic and cultural nuances of the Cantonese language, transforming market intelligence and social listening into actionable business insights.

MongoDB Atlas is at the heart of Votee AI’s remarkable innovation: the world’s first Cantonese LLM, which already serves a massive 86 million Chinese-speaking community globally. 

Building and scaling agentic AI platforms across different regions requires immense data flexibility, and this is why Votee AI decided to build on MongoDB. 

“MongoDB serves as the shared brain of our agentic AI platform,” said Dr. Leo Ma, Chief Scientist, APAC at Votee AI. “MongoDB is a strategic partner of ours, and the fact that we can deploy MongoDB across various global locations will definitely help our customers to scale their business.”

Omnichat: Unlocking massive AI scale

Omnichat is an omnichannel messenger platform that provides sophisticated social CRM, integrating seamlessly with major messaging applications like WhatsApp, Facebook, Instagram, and LINE.

The platform needs to capture and handle vast amounts of diverse client information and message data, which previously ran on a traditional relational database. However, the rigid nature of the relational model hindered Omnichat’s ability to manage unstructured data volume and the high-velocity read/write demands typical of real-time messaging.

By migrating to MongoDB Atlas, Omnichat modernized its data infrastructure, unlocking massive scale for the platform and increasing business value for its customers.

With MongoDB’s flexible document model, Omnichat was able to scale to 5 billion messages and drove $2 billion in client revenue with a 4.5 times conversion rate increase.

This is only the beginning of Omnichat’s growth and innovation plans. AI is now a core priority, and thanks to MongoDB Atlas Vector Search, the company built its new Omni AI agent.

“We chose MongoDB to help us easily scale our AI agent,” said Alan Chan, CEO and Founder of Omnichat. “It is all made possible through a stable, scalable data foundation.”

Great Wall Motor: Solving data complexity and security compliance

Great Wall Motor (GWM) is a pioneer in intelligent connected vehicles in mainland China. The company built the industry's first self-controllable Internet of Vehicles (IoV) cloud platform, integrating multiple Telematics Service Providers (TSPs) in mainland China. Today, the platform supports nearly 7 million connected vehicles and empowers users to perform a wide range of operations, including remote vehicle control, intelligent diagnostics, and emergency rescue.

Operating an IoV platform at such a large scale led to many data management and governance challenges that couldn’t be solved with traditional relational databases. GWM addressed these by modernizing its data architecture on MongoDB.

With MongoDB’s flexible document model, GWM was able to consolidate scattered data into intuitive JSON structures, drastically reducing maintenance costs while boosting query efficiency. MongoDB’s built-in geospatial indexing capabilities streamlined location-based services like charging station queries and geofencing, and horizontal scaling combined with automated data balancing now ensure over 99.99% reliability with zero user perception during updates or failures.

Furthermore, MongoDB’s built-in security capabilities enabled GWM to support HTTPS/TLS encryption to ensure data transmission security between the vehicle and the cloud, offering robust support for the SSL protocol. Sensitive data can be encrypted and stored securely, while encrypted search prevents any leakage of sensitive data information.

Finally, granular permission control mechanisms allow GWM to achieve multi-level authorization and segregated application of databases and collections, fully satisfying national IoV data regulation requirements and user privacy protection standards.

“MongoDB has not only solved our current data governance difficulties, it has also laid a solid technical foundation for the long-term development of GWM's intelligent connected business," said Zhonghua Jing, Head of Domestic Business Databases at Great Wall Motor.

Looking to the future, Great Wall Motor will continue to rely on MongoDB to explore LLM and AI use cases such as intelligent customer service and smart cockpits, supporting autonomous driving model training, simulations, and more, accelerating the transformation from IoV services to a full-value-chain digital intelligence platform.

Whether it’s building next-generation AI agents or securing massive IoV ecosystems, the path to sustained digital innovation requires a flexible, scalable, and secure data foundation. By migrating away from legacy constraints and modernizing on MongoDB’s flexible document model, organizations across Greater China are leading the way in building scalable, data-driven, secure, and compliant platforms that will shape our next digital decade.

*Source: https://www.morganstanley.com/insights/articles/china-ai-becoming-global-leader