Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
A global automotive manufacturer operates a fleet of several thousand development vehicles that generate 5 to 10 terabytes of measurement data, such as braking patterns and battery voltage, every week.
Unlocking insights from this massive data lake could take hours or days because only specialized IT staff had the skills to write complex queries....
“We’d solved access with modernization, but access alone doesn’t drive innovation. With multi-agent AI, engineers don’t just get data—they get insights they can act on immediately. Ultimately, the steps of data extraction and pattern recognition can be performed directly in a single step, and in natural language.”
Luxury vehicle and motorcycle manufacturer for premium consumer mobility.
Enterprise software, cloud infrastructure, and consumer electronics platform.
BMW's Vehicle data analysis is part of this use case:
Related implementations across industries and use cases
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
HR manually answered routine employee questions. Now, an AI assistant searches millions of documents to instantly provide 24/7 answers.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
Ad hoc queries bottlenecked specialists for days. Staff now ask questions in Teams and get sales data in seconds.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
A global automotive manufacturer operates a fleet of several thousand development vehicles that generate 5 to 10 terabytes of measurement data, such as braking patterns and battery voltage, every week.
Unlocking insights from this massive data lake could take hours or days because only specialized IT staff had the skills to write complex queries....
“We’d solved access with modernization, but access alone doesn’t drive innovation. With multi-agent AI, engineers don’t just get data—they get insights they can act on immediately. Ultimately, the steps of data extraction and pattern recognition can be performed directly in a single step, and in natural language.”
Luxury vehicle and motorcycle manufacturer for premium consumer mobility.
Enterprise software, cloud infrastructure, and consumer electronics platform.
BMW's Vehicle data analysis is part of this use case:
Related implementations across industries and use cases
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
HR manually answered routine employee questions. Now, an AI assistant searches millions of documents to instantly provide 24/7 answers.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
Ad hoc queries bottlenecked specialists for days. Staff now ask questions in Teams and get sales data in seconds.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.