Triage on a difficult day meant combing 14 systems under a regulatory clock. ORAI assembles the evidence; operators make the call.
A not-for-profit utility supplying water and wastewater services to most of Wales and parts of western England, receiving more than 1,800 telemetry alarms on a difficult day across around 14 operational systems.
When customers lose supply, operational teams work against a strict regulatory clock. Assessing an incident means pulling information system by...
“It is important to have the human in the loop at the right stages.”
Not-for-profit water and wastewater utility company for Wales.
Developed the ORAI operational AI proof of concept for Welsh Water's control room
Enterprise software, cloud infrastructure, and consumer electronics platform.
Welsh Water's Incident response is part of this use case:
Related implementations across industries and use cases
Crews wasted time verifying safety docs. A GenAI assistant now serves instant, authorized answers, scaling to 4,000 technicians.
Organizing tens of thousands of compliance documents bottlenecked audits. Now, AI structures files and drafts summaries for expert review.
Hours of system-hopping to find answers left nothing for analysis. Employees now ask in natural language—instant, structured results.
Hour-long dashboard delays hid sudden call spikes. Now, AI simulates staffing shifts so managers can fix service drops in seconds.
Pulling reports from scattered dashboards took two days. Now, employees query an AI assistant for instant commercial insights.
Two-person team, 10 power plants. Daily threat queries ate 2 hours; now agents run them while humans stay on consequential calls.
350,000 track images reviewed by hand each month, always chasing failures. TrackDefectX now catches defects before they escalate.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
QC simulations ran 15 hours and reset from scratch on every change. Digital twins cut that to 3.6 seconds.
Triage on a difficult day meant combing 14 systems under a regulatory clock. ORAI assembles the evidence; operators make the call.
A not-for-profit utility supplying water and wastewater services to most of Wales and parts of western England, receiving more than 1,800 telemetry alarms on a difficult day across around 14 operational systems.
When customers lose supply, operational teams work against a strict regulatory clock. Assessing an incident means pulling information system by...
“It is important to have the human in the loop at the right stages.”
Not-for-profit water and wastewater utility company for Wales.
Developed the ORAI operational AI proof of concept for Welsh Water's control room
Enterprise software, cloud infrastructure, and consumer electronics platform.
Welsh Water's Incident response is part of this use case:
Related implementations across industries and use cases
Crews wasted time verifying safety docs. A GenAI assistant now serves instant, authorized answers, scaling to 4,000 technicians.
Organizing tens of thousands of compliance documents bottlenecked audits. Now, AI structures files and drafts summaries for expert review.
Hours of system-hopping to find answers left nothing for analysis. Employees now ask in natural language—instant, structured results.
Hour-long dashboard delays hid sudden call spikes. Now, AI simulates staffing shifts so managers can fix service drops in seconds.
Pulling reports from scattered dashboards took two days. Now, employees query an AI assistant for instant commercial insights.
Two-person team, 10 power plants. Daily threat queries ate 2 hours; now agents run them while humans stay on consequential calls.
350,000 track images reviewed by hand each month, always chasing failures. TrackDefectX now catches defects before they escalate.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
QC simulations ran 15 hours and reset from scratch on every change. Digital twins cut that to 3.6 seconds.