Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
A global automotive manufacturer aiming for carbon neutrality by 2050 develops complex autonomous driving technologies that generate massive volumes of sensor and operational data.
On-premises infrastructure could not scale to handle increasing sensor data or link disparate analysis software for collision and aerodynamic tests....
“As vehicles become more advanced, the number of sensors will continue to increase significantly, control systems will become more complex, and reliance on software will grow.”
Global manufacturer of passenger cars, commercial vehicles, and electric vehicles.
Cloud computing platform and on-demand infrastructure services.
Nissan's R&D data analysis is part of this use case:
Related implementations across industries and use cases
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
A global automotive manufacturer aiming for carbon neutrality by 2050 develops complex autonomous driving technologies that generate massive volumes of sensor and operational data.
On-premises infrastructure could not scale to handle increasing sensor data or link disparate analysis software for collision and aerodynamic tests....
“As vehicles become more advanced, the number of sensors will continue to increase significantly, control systems will become more complex, and reliance on software will grow.”
Global manufacturer of passenger cars, commercial vehicles, and electric vehicles.
Cloud computing platform and on-demand infrastructure services.
Nissan's R&D data analysis is part of this use case:
Related implementations across industries and use cases
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.