Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
One of Asia's largest transit networks carries more than seven million daily commuters across 395 kilometers of track and 289 stations in the Delhi-NCR region.
Critical data was trapped in fragmented systems, forcing teams to rely on manual monitoring and reactive maintenance for assets ranging from rolling...
“We are using predictive maintenance for track, signalling gears, bearings of rolling stock, lifts, and escalators. Additionally, the Passenger Information Display System (PIDS) provides real-time updates, and the Communication-Based Train Control (CBTC) system on the magenta and pink lines improves train automation and safety. These projects collectively enhance efficiency, sustainability, and user convenience.”
Public rail transit network for Delhi and its surrounding satellite cities.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Helped DMRC build a Data Center of Excellence (DCoE) on Google Cloud.
Related implementations across industries and use cases
Crews chased breakdowns on 400km of track. Now, sensors predict failures, letting teams fix parts before service stops.
Engineers lost time to complex infrastructure. Automated scaling now cuts deployment cycles by 70% and halves build times.
CPU limits meant processing 100km of road video took 8 hours. Moving workloads to the cloud cut that time to under two.
Crews chased breakdowns on 400km of track. Now, sensors predict failures, letting teams fix parts before service stops.
Engineers lost time to complex infrastructure. Automated scaling now cuts deployment cycles by 70% and halves build times.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Auditors spent 10 months reviewing boxes of invoices. AI now reconciles the data in hours, freeing staff to investigate anomalies.
Advisors hunted data across five systems. GenAI now builds traceable meeting packs, saving 4,700 hours a year.
Without video, managers couldn't refute false claims or spot phone use. Now, AI dashcams flag risky habits to guide driver coaching.
Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
One of Asia's largest transit networks carries more than seven million daily commuters across 395 kilometers of track and 289 stations in the Delhi-NCR region.
Critical data was trapped in fragmented systems, forcing teams to rely on manual monitoring and reactive maintenance for assets ranging from rolling...
“We are using predictive maintenance for track, signalling gears, bearings of rolling stock, lifts, and escalators. Additionally, the Passenger Information Display System (PIDS) provides real-time updates, and the Communication-Based Train Control (CBTC) system on the magenta and pink lines improves train automation and safety. These projects collectively enhance efficiency, sustainability, and user convenience.”
Public rail transit network for Delhi and its surrounding satellite cities.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Helped DMRC build a Data Center of Excellence (DCoE) on Google Cloud.
Related implementations across industries and use cases
Crews chased breakdowns on 400km of track. Now, sensors predict failures, letting teams fix parts before service stops.
Engineers lost time to complex infrastructure. Automated scaling now cuts deployment cycles by 70% and halves build times.
CPU limits meant processing 100km of road video took 8 hours. Moving workloads to the cloud cut that time to under two.
Crews chased breakdowns on 400km of track. Now, sensors predict failures, letting teams fix parts before service stops.
Engineers lost time to complex infrastructure. Automated scaling now cuts deployment cycles by 70% and halves build times.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Auditors spent 10 months reviewing boxes of invoices. AI now reconciles the data in hours, freeing staff to investigate anomalies.
Advisors hunted data across five systems. GenAI now builds traceable meeting packs, saving 4,700 hours a year.
Without video, managers couldn't refute false claims or spot phone use. Now, AI dashcams flag risky habits to guide driver coaching.