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.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
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Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
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Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.
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.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
A new SUV launch generated massive lead surges. AI voice agents handled initial outbound calls, routing high-intent leads to human dealers.
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.