Kajima
Internal virtual assistant
Outsourcing restricted confidential data. A two-week sprint equipped teams with standardized workflows to securely build AI in-house.
- 20,000 employees using internal conversational AI
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
A global consultancy managing over 4,500 infrastructure projects relies on a digital twin platform to aggregate complex data from IoT devices and enterprise systems.
Non-technical users struggled to navigate thousands of data points or extract insights manually from the centralized system. This complexity...
“We handle complex projects such as airports, bridges, hospitals, and universities. We’ve even helped plan cities.”
Architecture, engineering, and planning consultancy for global infrastructure projects.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Dar Al-Handasah's Building data analysis is part of this use case:
Related implementations across industries and use cases
Outsourcing restricted confidential data. A two-week sprint equipped teams with standardized workflows to securely build AI in-house.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
L&T's AI couldn't break out of pilots across 140,000 employees. Microsoft Copilot now serves 23,000+ daily; HR resolution up 70%.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Surging delinquency burdened staff. Now, an AI assistant handles routine collections, freeing teams for high-touch, in-person engagement.
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.
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
A global consultancy managing over 4,500 infrastructure projects relies on a digital twin platform to aggregate complex data from IoT devices and enterprise systems.
Non-technical users struggled to navigate thousands of data points or extract insights manually from the centralized system. This complexity...
“We handle complex projects such as airports, bridges, hospitals, and universities. We’ve even helped plan cities.”
Architecture, engineering, and planning consultancy for global infrastructure projects.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Dar Al-Handasah's Building data analysis is part of this use case:
Related implementations across industries and use cases
Outsourcing restricted confidential data. A two-week sprint equipped teams with standardized workflows to securely build AI in-house.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
L&T's AI couldn't break out of pilots across 140,000 employees. Microsoft Copilot now serves 23,000+ daily; HR resolution up 70%.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Surging delinquency burdened staff. Now, an AI assistant handles routine collections, freeing teams for high-touch, in-person engagement.
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.