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.”
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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.
Each new agent took 8 weeks to ship reliably. A factory framework cut that to days, freeing people for the relationship work AI can't do.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
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.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Equipment faults left technicians hunting for technical data while machines sat idle. A chatbot now puts the answer in their hands.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
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.
Each new agent took 8 weeks to ship reliably. A factory framework cut that to days, freeing people for the relationship work AI can't do.
Rebuilding apps for iOS took a month. AI now generates code directly from Android logic, cutting the adaptation cycle to a week.
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.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Equipment faults left technicians hunting for technical data while machines sat idle. A chatbot now puts the answer in their hands.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.