Nissan
Software development platform
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
- 75% reduction in software test execution time
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
A Chinese auto giant producing modern vehicles that rely on thousands of complex software modules.
This heavy reliance on software made vehicle development increasingly complex and time-consuming. Engineers needed a more efficient way to manage...
“With AI's assistance, the overall efficiency of software development has improved by about 30 percent compared to the traditional method. For coding tasks specifically, we're seeing efficiency gains of up to 50 percent.”
Also reported by
Multinational automotive group manufacturing passenger cars and electric vehicles.
Geely's Software development is part of this use case:
Related implementations across industries and use cases
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.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
A new SUV launch generated massive lead surges. AI voice agents handled initial outbound calls, routing high-intent leads to human dealers.
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
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.
Thousands of software modules slowed vehicle development. Now, engineers collaborate with 64 AI agents to write and debug code.
A Chinese auto giant producing modern vehicles that rely on thousands of complex software modules.
This heavy reliance on software made vehicle development increasingly complex and time-consuming. Engineers needed a more efficient way to manage...
“With AI's assistance, the overall efficiency of software development has improved by about 30 percent compared to the traditional method. For coding tasks specifically, we're seeing efficiency gains of up to 50 percent.”
Also reported by
Multinational automotive group manufacturing passenger cars and electric vehicles.
Geely's Software development is part of this use case:
Related implementations across industries and use cases
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.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
A new SUV launch generated massive lead surges. AI voice agents handled initial outbound calls, routing high-intent leads to human dealers.
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
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.