Digitize Asset Performance
from Day-One to End-of-Life
Unplanned downtime reduction
87%
Non-productive time reduction
52%
ALM prediction accuracy
91%
Bring operational context to your sensor data
Build Condition-based Maintenance (CBM) predictive algorithms that understand operational context through integration of operational, maintenance, and sensor data.
Context-aware CBM
Predict component life months in advance using your operational data
Prescient’s proprietary Asset Life Model (ALM) monitors and predicts component performance from the day they are put into service, and can predict component end-of-life months in advance.
Asset Life Model
Smart Alerts
Combine data and AI to generate simple, actionable instructions for the field team
Prescient’s Smart Alerts improve the performance of less-experienced field crews, ensure consistent performance across all crews, and enforce best maintenance practices based on data science.
Enable supply chain planning
and vendor quality comparison
Prescient’s Asset Life Model (ALM) normalizes performance of components used under different operating conditions, making fair comparison of component performance possible for the first time.
Performance Normalization
Delivering business impact
Precision Drilling leverages the power of real-time data to optimize their critical drilling processes.
Optimizing instrument utilization
The manufacturer and Prescient built a pilot in under 2 weeks and delivered it to the end customer.
“Prescient's low-code platform and domain knowledge enabled a level of innovation and execution unheard of not only in the drilling industry but the broader energy industry. We look forward to pursuing more projects with Prescient and challenging the status quo.”
Russell Whitney, IIoT Manager at Precision Drilling