Geely
Software development
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
- Up to 50% efficiency gain for coding tasks
- ~30% improvement in software development efficiency
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
Great Wall Motor is a global automotive technology company operating multiple brands across more than 170 countries and managing 14 global cloud environments.
The organization faced significant challenges maintaining unified security governance and compliance standards following a 50% reduction in its...
“Deploying the security compliance system on AWS China using Amazon Q Developer and AWS Graviton4 enabled measurable improvements in development efficiency, cost structure, and system stability, with elastic scheduling contributing to sustained savings. A consistent architecture across overseas and China regions supported the unification of GWM’s global technical framework. During the migration, standardized managed services reduced operational complexity, allowing the team to focus on advancing security capabilities and supporting ongoing business growth.”
Global automotive manufacturer specializing in SUVs, pickup trucks, and electric vehicles.
Cloud computing platform and on-demand infrastructure services.
Great Wall Motor's Security compliance system development is part of this use case:
Related implementations across industries and use cases
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
Every alert still needed command-center follow-up — a ceiling as fleets grew. FleetGPT now reasons over each event and acts, not just flags.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
Great Wall Motor is a global automotive technology company operating multiple brands across more than 170 countries and managing 14 global cloud environments.
The organization faced significant challenges maintaining unified security governance and compliance standards following a 50% reduction in its...
“Deploying the security compliance system on AWS China using Amazon Q Developer and AWS Graviton4 enabled measurable improvements in development efficiency, cost structure, and system stability, with elastic scheduling contributing to sustained savings. A consistent architecture across overseas and China regions supported the unification of GWM’s global technical framework. During the migration, standardized managed services reduced operational complexity, allowing the team to focus on advancing security capabilities and supporting ongoing business growth.”
Global automotive manufacturer specializing in SUVs, pickup trucks, and electric vehicles.
Cloud computing platform and on-demand infrastructure services.
Great Wall Motor's Security compliance system development is part of this use case:
Related implementations across industries and use cases
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
Every alert still needed command-center follow-up — a ceiling as fleets grew. FleetGPT now reasons over each event and acts, not just flags.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.